June 24, 2022 O-06-022--RT-01
A big challenge is addressing the development and manufacturing of advanced therapies. Pipelines of cell and gene therapies are increasing, and their complexity demands new methods and real-time analytics for process efficiency and predictability. An end-to-end connected bioprocess is required, which is a key component of Biopharma 4.0. All systems and equipment need to be connected digitally to run, control, and improve the process via feedback loops and machine learning / artificial intelligence. Our challenge is to put these technologies in place now to keep up with demand and to be ready as U.S. FDA guidelines turn into regulations.
One of the biggest challenges that our industry faces is with the supply chain. This issue has been exacerbated by the COVID-19 pandemic as well.
The longer it takes to get supplies to develop pharmaceuticals, the longer it takes to bring a product to market. For developers and pharma companies, this can mean the difference between being first to market or coming out behind other established products, risking the loss of permanent market share that the company needs.
When you work with CDMOs with a global network, like AGC Biologics, we have extensive material sourcing resources, effective bargaining power, and a worldwide inventory of supplies to leverage. These characteristics provide us with the flexibility and power to develop and manufacture your product — even during a pandemic-induced supply shortage.
One thing that we are very proud of at AGC Biologics is our ability to address our clients’ needs. It is this knowledge and experience with managing challenges that enable us to resolve any issues during the development and manufacturing process and meet important clinical and commercial deadlines.
Decreasing the cost of bringing new biologic entities (NBEs) to market and improving R&D cycle times remain the biggest challenges in the industry. Right now, that cost stands at $2 billion per NBE and an average of seven years of development. To drive a more productive future for R&D with more equitable and quick access to new therapies, the industry should continue to nurture collaborative work, expanded use of novel analytical tools, wider adoption of digital technologies, and streamlining of drug development protocols.
The COVID-19 pandemic disrupted supply chains worldwide, with cascading impacts that led to global shortages of goods and materials. Pharmaceutical shortages — especially for compounds classified as “essential medicines” — became perhaps the most pressing and urgent challenge to solve, with the lack of critical medicines disproportionately affecting the world’s most vulnerable populations.
Pharma has long needed new, agile manufacturing technologies and methods to overcome medicine shortages, respond to sudden spikes in demand, and address long-term sustainability concerns. While the broader pharma industry has tried to optimize supply chains to cut costs and make production lines viable, it has relied on legacy technologies for many decades and has been slow to embrace new production approaches. This is particularly evident in the case of plant-based medicines, which rely on traditional agricultural cultivation and are therefore vulnerable to variables such as climate events, pest and disease issues, soil health, geopolitical crises, and more. As a result, many active pharmaceutical ingredients (APIs) — and the common and essential medicines they’re used to produce — have a fragile supply chain that is unpredictable, inefficient, and expensive.
Thanks to new advancements in biomanufacturing and synthetic biology, what typically takes years and happens almost exclusively outside of the United States can now be done on demand in weeks, at a lower cost, and domestically. We now have the ability to transform the pharma supply chain and overcome one of pharma’s most pressing challenges to provide patients and doctors with essential medicines when and where they’re needed.
Currently, the pharma/biotech industry is facing challenges in the capital markets due to the undervaluing of companies. Fortunately, with time, the capital markets will ultimately correct themselves, and funding will continue for companies with innovative medicines to treat unmet medical needs; however, an even greater challenge is standing out among the competition in an already crowded market. A key differentiator for successful companies will be their ability to deliver truly transformative medicines. Developing drugs that work will not be enough to set companies apart. The therapies need to improve the patient’s health and be simple and convenient to administer. For example, wet age-related macular degeneration (wet AMD) and diabetic macular edema (DME) patients require an injection into the eye every 6–8 weeks, administered in a doctor’s office, to prevent disease progression and blindness. For patients, an injection into the eye is not only uncomfortable but also requires time or another person to provide transportation to and from the appointment, which can be a burden.
At Ashvattha Therapeutics, our approach is to not only focus on making precision medicine more precise but also be a disruptive treatment for diseases with a high patient burden. Our clinical candidate designed to treat wet-AMD and DME, D-4517.2, stands to relieve patients of this uncomfortable injection directly in the eye by providing a once per month subcutaneous injection, similar to insulin injections, that patients can self-administer in the comfort of their home.
The industry needs to address the issues around sustainability, resource management, process design, and process efficiency, which will become increasingly important. The challenges observed with the availability of critical components for up and downstream manufacturing, particularly disposable plastics, must be considered when designing new pharma processes, from discovery through clinical and beyond.
A clear challenge of the pharmaceutical industry has been highlighted by the recent pandemic, and that is the overreliance on single-sourced materials and vulnerabilities within the global supply chain. Like any other manufactured product, pharma and biopharma products are a sum of the parts, and missing any one individual component can ultimately lead to a critical drug shortage. However, what is unique to the pharmaceutical industry is the exceptionally high quality and regulatory standards. Therefore, a system built for the health and safety of patients can unfortunately make it challenging to quickly substitute missing ingredients, alter a process, or change manufacturing sites. Consequently, building up resilience and redundancy into supply chains, as well as a pivot to reliability over cost (including onshoring) of pharmaceutical manufacturing, will rapidly become a key focus and a perhaps the biggest short-term challenge of the industry. Building further upon this, many ingredients utilized in the rapidly expanding biopharma space are single-sourced, not necessarily made to cGMP standards, and not entirely fit-for-purpose. This leaves an enormous challenge of ensuring reliable supply for dozens if not hundreds of components, and therefore perhaps an order of magnitude more complicated than historical small molecule drug sourcing. Thus, the challenge of building and launching innovative treatments will be only as good as our ability to build redundancy and reliability into the ingredient supply for the patients that ultimately depend on them.
Healthcare inequity. If you look at a map of the United States and ask where high-quality healthcare is accessible to the broadest populations, the U.S. looks like a checkerboard, with vast “healthcare deserts” and millions located many miles from the care that those in more affluent areas often enjoy. This is not a failure of medicine but a failure of business model. Centralized care, where testing is available often in brick-and-mortar locations (doctor’s offices, hospitals, pharmacies, etc.) requires that people come to the care rather than the care coming to the people. For a mom who cannot get childcare, a veteran who can’t come into a VA hospital, or a college student who is too embarrassed or afraid to come into a student health clinic for testing, this “last mile” challenge creates real barriers to high-quality care delivery and outcomes. There is no shortage of great (awe-inspiring) technologies on the market. Looking at “how” care is delivered is as critical to healthcare equity as “what” care is delivered. This will be critical to ensuring access to reaching the many underserved today.
The current global supply chain issues are an unresolved challenge for the pharmaceutical industry. The pandemic has put stress on the supply chain and manufacturing, forcing the adoption of new technologies, regardless of the regulatory burden that this implies. Although the concept of portable, continuous, miniature, and modular manufacturing units has become a reality, it is not yet accessible across the pharmaceutical and biopharmaceutical ecosystem.
Bruker has joined forces with NovAliX, Alysophil, and Dedietrich Process Systems to bring to market a new approach to active pharmaceutical ingredient (API) production. The partnership aims to provide a complete, standalone, and location-independent API manufacturing solution to a pharmaceutical company or contract manufacturing organization. The partnership will leverage combination breakthrough synthesis, continuous flow chemistry, and in-flow analysis with artificial intelligence to create this next-generation, autonomous, and optimal production unit.
Unfortunately, there are multiple manufacturing bottlenecks that create a major obstacle for development across the entire field. First, there’s a major talent crunch in the pharmaceutical and biotech world; the demand for skilled labor far outpaces supply everywhere. As the industry progresses, and more therapeutics are U.S. FDA–approved for larger patient populations, the need for larger manufacturing teams of highly skilled professionals becomes even more acute. It can take months to identify and hire the right personnel, and then up to nine months to train someone on GMP manufacturing processes, but unfortunately the average employee retention is only a year and a half.
This is very inefficient and a major pain point for cell therapy manufacturers. The introduction of automated technologies, like the Cell Shuttle, will allow smaller teams to manufacture more products. Particularly in cell and gene therapy manufacturing, labor is a major contributor to the manufacturing cost per dose. It's widely acknowledged that cell therapy manufacturing is a lengthy, time-consuming, and expensive process. Current processes require teams of highly trained professionals spending weeks in expensive cleanrooms, executing on the order of 50 manual processing steps on a plethora of benchtop instruments — all to produce one therapy for one patient at a time.
Additionally, human error invariably leads to manufacturing issues. Some manufacturers have reported process failure rates of up to 18%. The introduction of true end-to-end automation will help accelerate and improve cell therapy manufacturing and alleviate the shortage of qualified personnel.
Developing novel therapies and bringing them to physicians and patients is a long and difficult process. Drug development remains one of the highest-risk processes within the life sciences industry, with approximately 10–15 years of clinical work necessary to bring a compound from discovery to patients, and with most therapies never making it through development due to lack of efficacy / tolerability issues. Diseases related to neurodegeneration and psychiatric disorders bring another level of challenge for scientists, given the complexity of the brain.
Historically, most scientific and technological approaches have lacked the specificity and precision with which to identify and validate new targets to develop therapies to alleviate symptoms or treat neurodegenerative disorders. The current standard for drug development for central nervous system (CNS) or neurodegenerative disorders has been to utilize mouse models; however, because of the brain’s complexity, this approach has significant shortcomings. Additionally, because the pathophysiology for many CNS disorders remains unknown, drug development is a lengthy and costly process that is accompanied by a high degree of uncertainty that drugs in development will succeed. At Cerevance, we are focused on tackling these shortcomings and are using postmortem brain tissue combined with machine learning to discover key biomarkers that play an influential role in neurological disease progression and the specific brain circuits and/or cells that are disrupted by neurological disease.
To foster new and interruptive methods for treating neurodegenerative diseases, it is critical that more precise, highly specific means be implemented while placing a greater emphasis on the utilization of human data.
The discovery of new therapies is hugely expensive, with cost estimates ranging from $2–4 billion. The economics of pharma and biotech is placing the discovery of new drugs under enormous strain, which represents a significant and immediate challenge. This has been brought into focus by the debate around antibacterial drugs. It is readily accepted that the absence of new antibiotics will turn routine infections and operations into life-threatening conditions. Despite this, few new antibiotics have reached patients in the last decade, and the primary reason is the uncertainty over recouping research and development costs. Even the advent of precision medicine, hailed by many as a huge advance for previously untreatable conditions, is challenging the economics of pharma and biotech. Therapies can require expensive and complex cell manipulations for the treatment of, in extreme cases, a single patient. The onus is on pharma and biotech to reduce the costs of discovery and development of new therapies, where efficacy and safety are still the biggest reasons for clinical attrition. Big data, machine learning, and artificial intelligence promise much in identifying optimal disease intervention points and pressure testing biochemical pathways from a safety perspective to drive down attrition rates and hence reduce costs. Identifying cheaper and scalable manufacturing processes is also key to democratising healthcare. The onus is on pharma and biotech to become more efficient and reduce costs by the adoption of new technologies and ideas rather than demanding that individuals, insurance, and healthcare providers pay more and more to access treatments.
Diverse patient populations, whether defined by race, ethnicity, gender, geography, or socioeconomic factors, have historically been underrecruited in clinical trials — an issue that is currently top of mind for the pharma and biopharma industry. This is a multifactorial issue that can be driven by proximity to trial sites, cultural preferences, health literacy, language barriers, income, access to transportation, or ability to take time from work to receive care. While past approaches using traditional clinical trial sites yield predictable results, they also yield low recruitment of diverse patient populations. The industry needs new approaches, using real-world data and advanced analytics, to locate and engage with underrepresented patient populations.
Clinical trials are the evidence that a drug will be effective and safe in a patient population. Given the diversity of the U.S. population, it’s important that clinical trials demonstrate the same clinical endpoints across an equally diverse study population. In addition, as pragmatic clinical trials look beyond the science of the drug into the effectiveness of how therapies are delivered, it’s equally important to look at the drivers of healthcare disparities and identify opportunities to address them to truly move the needle toward more diverse recruitment in clinical trials.
The pipeline of biomedical innovations has been exceptionally strong across many diseases. However, lower clinical trial access to patients, the pandemic further diminishing patient participation and new study starts, limited research infrastructure and budgets at healthcare providers, and rather burdensome legacy trial technologies have reduced the throughput potential for these innovations. These inefficiencies are, in part, increasing the cost of new medicines and lowering the pace of patient access to the latest innovations. Looking ahead, we have the tools for a better way of operating. Providers at the community and regional health levels are eager for new ways of working and supporting efficient research operations. While some of the new AI digital solutions for patient matching to trials, decentralized solutions, and digital integrated solutions lack certain functionalities of legacy systems, they offer performance, acceleration, and cost advantages unachievable by these older technologies. As the pipeline accelerates, evidence is generated more rapidly, value will improve, and outcomes benefits will accelerate. So, to the spirit of the question, this presents the biggest challenge and the highest promise.
Healthcare is generally a reactive field, rather than a proactive one, and that tends to drive thinking in biopharma as well. This plays out as a focus on treatment over prevention, effectively engineering fixes instead of preventing problems.
There’s a paradigm shift underway, though, fueled by new technology. Many see opportunities for early intervention for better living, saving lives, and preventing problems.
In the cell therapy manufacturing space, we’ve seen how this thinking has led to real challenges. In the decade since the first cell therapy clinical trials began curing patients, the main approach to scaling up for patients has been to focus on scaling up patient cells ex vivo. To do so, myriad engineering steps have been tested and employed, with the goal of producing enough therapeutic cells after the fact, with mixed results.
Accumulating data suggests that younger cells can be more potent than engineered cell populations that have been expanded over the course of weeks. New technologies like microfluidics will change this landscape altogether, by capturing greater numbers of more-potent naive cells from patients to be turned into medicines faster.
Time will tell if an approach like this will make the lengthy, manual, and burdensome expansion steps obsolete. But there’s clearly an urgent need for the entire industry to shift its mindset.
Cytiva has done some interesting research here — we surveyed hundreds of industry leaders for our Biopharma Resilience Index to find the top five areas of priority. They are supply chain, talent, strength of the R&D ecosystem, quality and agility in manufacturing processes, and government policy. The underlying challenge across these priorities is: how do we effectively harness digital and automated solutions?
As our industry incorporates more digital and automated solutions, we have begun to generate and accumulate an enormous volume of process data, and we need to turn those data into decisions. To be useful, data need to come with context about what they describe and how events in upstream and downstream processes relate. Currently, data sets are being collected and stored in various databases or on the instrument itself. Moving the data to a central location will not solve the problem — data must be written in comparable formats with comparable context (i.e., written in the same “language”). Today, there is no such language common to suppliers, leaving our industry without interoperability between data sources.
This interoperability would allow for “smart” suppliers and a “smart” supply chain. A smart supplier is one who understands that data, as assets, are supplied and consumed along the value chain alongside physical products. As such, smart suppliers create products that integrate into customers’ data systems, enabling suppliers and their customers to capture, curate, and harness those data for superior products, higher efficiencies, and reduced supply chain risk, all at lower overall costs.
The push to create a “smart” bioprocessing ecosystem has been difficult because it requires a coordination of change — a kind of phase transition to a new way of working. It requires vendors to supply equipment and control systems that speak a common language, data systems that aggregate data and their context, and analytics that generate insight from it all. The good news is that the pace is quickening, with more companies building data capabilities and standards into their fundamental way of working.
The biggest challenge the pharma/biopharma industry currently faces is what we call the data–insight gap. The volume of human molecular data is growing exponentially, but our analytical capabilities are growing linearly, at best. The result: timely, expensive, and inefficient ways to develop drugs. At CytoReason, we develop computational disease models capable of digesting, organizing, and making sense of multiple data types and sources from multiple diseases and treatments. These disease models are created by leading biologists and bioinformaticians, and they are backed by top-tier publications with the latest omics data and cell-focused natural language processing. The data in the models is broken down by each disease indication, tissue type, patient population, and disease severity. Our artificial intelligence technology then turns this big data into useful, actionable insights, so that pharma companies can make drugs faster, more cheaply, and more efficiently. CytoReason is one of the few companies that provides a comprehensive map of human diseases. Our disease models allow for comparisons across treatments, patient groups, and disease mechanisms, using deep mRNA data. The insights give scientists a bird's-eye view of entire drug portfolios.
The reliance on manual and siloed processes across all areas of drug development continues to hold the life sciences industry back. We have seen remarkable progress over the last two years in accelerating digital transformation in clinical development, but there remain significant opportunities to take the volumes of new data streams available in trials and turn them into insights and evidence about new therapies exponentially faster. The process of clinical development continues to be too slow and too costly to allow the industry and patients to fully benefit from the coming wave of immunotherapies that have the opportunity to transform human health. Adopting new technologies, digital trial models, and analytics and AI at scale to keep up with the scientific breakthroughs that are coming remains our biggest challenge.
Drug discovery, development, and clinical trials are more complex now than they have ever been before, ironically due to the innovations in characterizing biochemical, hormonal, and genomic factors that impact patient health. Patients are located around the globe, so data is cascading in from a variety of sources, including real-world evidence, wearables, imaging, biomarker labs, and electronic patient-reported outcomes (ePRO) / electronic clinical outcome assessment (eCOA). The technology used by the industry has not kept pace with the advancement of today’s modern world. Existing combined solutions are unable to meet the challenges and adjust to the dynamic world of decentralized trials (DCTs), digital transformation, and data science.
The industry needs a single source of truth to analyze, process, and visualize data, in real-time, so that DCTs can run seamlessly and ensure clean, accurate data they can trust. One that can capture the range of different data types that are needed, whether that be from traditional sources or more innovative data points. Encapsia was designed with all this in mind, to help implement a single platform, offering all parties a holistic and real-time view of all their trial data, with visibility of trends across patients, sites, and trials.
In an increasingly noisy digital environment, pharma companies face their biggest challenge in delivering the right message. Pharma companies need to reach the right clinician at the right time to impact point-of-care decisions that result in optimal patient outcomes. However, the speed of AI/ML, science, and drug discovery is rapidly increasing by the day, and clinicians are being inundated by the flow of information to their screens and inboxes. This creates a narrowing window of opportunity to craft the ideal engagement opportunity with clinicians. Pharma marketers have to determine how they can craft personalized campaigns that cut through the noise and information-overload facing clinicians.
When considering the largest challenges faced by industry, it is first important to distinguish between large pharma and smaller companies. Small pharma and biotechs tend to be more comfortable with risks in developing innovative therapies, but the single greatest challenge facing small industry is an ongoing need to secure capital. This requires striking the right balance between risk and reward for investors. Higher-risk therapies require a large market size and patient need as well as likelihood of reimbursement to ensure that companies can provide a return to investors given the large risks they are taking.
In many cases, this means an initial focus in disease areas that have validated targets and are well researched before securing funding to explore the use of therapies in these diseases. However, once the challenge is met in attracting investment to pursue the promise of a therapy, this opens greater opportunity for other indications to pursue that can benefit ever-broader patient populations.
We are living this experience at EyePoint, where our experimental therapy is first undergoing clinical trials in wet age-related macular degeneration (wet AMD). We are then working to explore the treatment potential in several other eye disorders, including diabetic retinopathy, diabetic macular edema, and retinal vein occlusion. As we continue to instill confidence in the potential of our therapy, we are excited to potentially benefit a large number of patients with serious eye disorders.
The industry is currently facing challenging market conditions. Securing the funding necessary to continue to develop and advance product candidates is more difficult in these circumstances. I have spoken to several other industry leaders who are feeling pressures around meeting their performance goals in this environment. It is a collective challenge under normal conditions but certainly exacerbated by these unprecedented market conditions across many companies of different sizes and stages.
Additionally, we’re seeing ripple effects of the COVID-19 global pandemic and how companies have had to change their working models over the past 2+ years in ways they likely never imagined. And now we are all challenged on how practically to shift back to a semblance of original practices in a safe and efficient manner while maintaining elements of the alternative methods of conducting business that have emerged.
Supply chain issues remain challenging, and recovery and stabilization, I fear, are many years away. Many small companies have faced challenges like this before, but supply chain issues are affecting companies at large. Challenges are, in some ways, beneficial because they encourage you to consider different paths that you may not have thought about otherwise. In remaining flexible, you can find yourself in a unique situation that is sometimes better than your originally intended destination.
The pharmaceutical industry is undergoing rapid changes due to the development of several technologies. The prominent trends include artificial intelligence (AI), automation, and other industry 4.0 technologies. GSK is investing in AI, also through external collaborations, with the aim of reducing the time and money needed to develop the medicines and vaccines of the future. Having the right talent with deep expertise across a number of relevant areas will continue to be a key factor in achieving these goals.
There is also an opportunity to demonstrate the value of innovation in the pharma industry to the public and key decision makers. As the COVID-19 pandemic has shown, the public health impact of effective preventative and therapeutic solutions for infectious diseases is significant, yet the costs and lead times of developing those treatments can be further reduced. The emphasis on health resilience and the role that preventative care can play in improving health outcomes is likely to increase. For example, vaccination programs represent significant value for societies, as they typically have significant impact and are cost effective.
Companies across all sectors are increasingly focused on optimizing the social and environmental impact of their operations. GSK set ambitious new environmental sustainability goals at the end of 2030 and has established an enterprise transformation program addressing climate, water, waste, and biodiversity across our operations.
Currently, the high cost of advanced biotherapies reduces the size of the addressable target population. There are several challenges that must be overcome to bring biologic drugs to market. For instance, proteins and monoclonal antibodies are experiencing increasing pressure from drug pricing standards and patent cliffs, while cell and gene therapies often face scale-up challenges and industry-wide capacity restraints.
Cell and gene therapies continue to fuel the biopharma pipeline. However, there are significant challenges pertaining to the inherent variability of cells, the personalization of drug therapies, and the broad range of technologies utilized. While CMC standards for cell and gene therapies are well-established for proteins and monoclonal antibodies, they are not yet befitting and pose a significant obstacle in obtaining biologics licensing applications (BLAs).
In the Pharma Solutions division of IFF, we’re learning more about how our excipient expertise can add value to this burgeoning space. Backed by decades of expertise in polymer design, we bring formulators and drug manufacturers solutions and expertise to navigate the current and future challenges — in small and large molecules — as well as in the biologic drug development space.
There are numerous challenges that pharma/biopharma companies are facing and will continue to face going forward. They include supply chain and staffing issues, adapting to emerging technologies such as continuous manufacturing and 3D printing, and the knowledge gap that continues to widen related to material science and excipient technology in particular. With time, supply chain and staffing issues will resolve themselves. This should open numerous opportunities for renewed product development. Regarding new technologies, and continuous manufacturing specifically, implementing new equipment requires capital expenditures and an understanding of the differences between batch and continuous processing. With the various initiatives and opportunities, one challenge that continues to grow is the knowledge gap in material science and excipient technology, in part, due to fewer academic institutions performing research in the area of excipients. And, as excipients are critical to successful drug product development and manufacture, excipient knowledge is essential. Partnerships between drug product manufacturers and excipient suppliers, distributors included, help bridge the knowledge gap. Understanding excipient performance and the synergies that some excipient combinations create can enhance drug product quality and performance, leading to an effective therapy. This is true regardless of dosage form type and design or route of administration.
The pharma and biopharma industries’ biggest challenge is also one at the healthcare provider site level: technology needs to be an enabler that empowers the human worker and moves healthcare forward by making intuitive decisions automatically. Transforming the patient journey is the responsibility of the entire healthcare and life sciences ecosystem. Through modern technology and expertise, we are able to equip healthcare providers, clinical research coordinators, and care teams with access to AI-enhanced patient insights like never before.
The key is that this information must be useful and presented at the right time and in the right format to streamline and accelerate complex clinical trial processes from feasibility to prescreening and connecting eligible patients to the trial that’s best for their unique situation. The response to this certainly should not be adding “more technology” without purpose. Instead, we must harmonize the data that we have, thoughtfully ensuring that users are augmented based on the information already at their disposal; taking waste out of healthcare and clinical trial processes; and delivering better outcomes that are more meaningful to patients, caregivers, and researchers.
The lack of good new targets and new approaches to the biology of disease in a few major cases is a major challenge. Neurodegenerative disease is a great example, where it seems likely that the mechanisms that we have been targeting with considerable effort may not be the right ones; this work is challenged because our models of disease in most cases are quite poor. Another major area is around the age-related degeneration of lung function. Here, the lack of success I attribute more to lack of attention, say, as compared to cancer, as there is an order of magnitude fewer different cell types involved and the models are better; however, unlike cancer, where a handful of universal treatments seems less feasible, a handful of treatments for most of declining pulmonary function may be more achievable. Declining pulmonary function with age and exposures is of similar significance in morbidity and mortality to cancer as a whole, neurodegenerative conditions, and cardiovascular disease, so it's worth the continued effort.
Scalability is one of the biggest challenges facing the biopharma industry. My background in bioengineering taught me the importance of innovations that don’t solve just one problem but have the potential to solve many. Oftentimes, medical solutions such as autologous cell therapies and organ transplants are a one-to-one fix — one treatment is developed at a time for one patient. We need one-to-many solutions to more efficiently treat patients with life-threatening illnesses. Within the organ disease ecosystem, Satellite Bio is developing a regenerative solution that can turn a single organ into many Tissue Therapeutics with a minimally invasive procedure. And Satellite Bio is also scalable across disease spaces and implementation. While the company’s first product is aimed at treating chronic liver disease, it’s not limited to just one organ type; Satellite’s platform has the potential to explore the application of Tissue Therapeutics in other cell types. Satellite anticipates that the procedure for patients to receive SATs will be much less invasive than an organ transplant, accelerating the rate at which patients can receive treatment. Innovative, lifesaving, and scalable treatments are necessary and important to ensure that they are able to rapidly reach the hands of patients in need.
One of the main challenges we observe today is that the complexity of small molecules in the pipeline is increasing. Twenty years ago, a 3–5 step synthesis was considered the norm. In comparison, today it is not rare to have more than 20 steps during synthesis, including several advanced building blocks. This presents a supply chain challenge; each molecule requires a specific supply chain strategy including potential fallback scenarios. For our clients, partnering with experts in the field who can support beyond pure technical capabilities immensely helps navigate this landscape — this is especially true for small emerging biotech companies.
Of course, the COVID-19 crisis has been and still is a challenge to our supply chain. In the beginning of the pandemic, the focus was concentrated on the availability of personal protection equipment. Over time, it has shifted to the timely delivery of raw materials, especially from suppliers in Asia. One of the methods we’ve employed at Lonza is implementing a thorough tracking system for material supply that allows us to spot potential risks ahead of time and address them before they escalate.
Lonza’s global small molecule network has multiple sites across three regions: the Americas, Europe, and Asia. This allows us to guarantee backup solutions from different continents and secure supply chains. Our fully integrated offering enables a simplified supply chain with shorter and accelerated timelines, spanning drug substance to drug product development and manufacturing, including particle engineering, solid-state services, and bioavailability enhancement.
High rates of clinical failure in late-stage drug development are a consequence of multiple factors; one of the more significant factors is the lack of effective translation of biology from preclinical (non-human) proof-of-concept testing to mirror the human condition. Metabolomics is the single, unique omic that is sufficiently phylogenetically conserved across species, providing the ideal platform for seamless translation of biology from preclinical model systems to humans. Inclusion of metabolomics to augment genomics and proteomics technologies will provide significant synergies in establishing molecular benchmarks of efficacy and have significant impact on new drugs under development.
Metabolomics, the large-scale study of all small molecules in a biological system, is the only omics technology that provides a complete current-state functional readout of a biological system. Metabolomics helps researchers see beyond the genetic variation of individuals, capturing the combined impact of genetic and external factors such as the effect of drugs, diet, lifestyle, and the microbiome on human health. By measuring thousands of discrete chemical signals that form biological pathways in the body, metabolomics can reveal important biomarkers, enabling a better understanding of a drug’s mechanism of action, pharmacodynamics, and safety profile, as well as individual responses to therapy, ultimately leading to better drug development and true precision medicine. Metabolomics both deconvolutes and enhances other omics technologies, ensuring that genomics and proteomics investments are fully captured.
While emerging biotechs face their own set of challenges, contract development and manufacturing organizations (CDMOs) are challenged with standardizing production for novel modalities such as cell and gene therapies (CGT), improving yield and scalability, and ensuring that processes follow current good manufacturing practices (cGMP) and regulatory standards.
The U.S. FDA predicts that it will approve 10–20 CGT products per year by 2025. These innovative therapies offer the potential for one-time treatments to cure diseases and conditions that were historically untreatable. And what’s exciting is that CGT has just started on its industrialization journey, with plenty of opportunities to improve the efficiency and robustness of processes. For example, no template currently exists to produce these therapies. Manufacturers must carve out their own paths from development to production and approval. Our goal in product and technology innovation is to shorten the process of moving lifesaving therapies into the clinic and to patients faster. For instance, our VirusExpress™ lentiviral production platform increases dose yields and reduces process development time by approximately 40%.
Additionally, the industry continues to work toward a fully automated Bioprocessing 4.0 for monoclonal antibody therapies. Our focus here over the past several years has made great strides in intensifying processes, developing and integrating software for automation and data retrieval, and incorporating real-time in-line testing. The next generation of processing will be an evolution that will afford manufactures more speed-to-market, facility flexibility, and cost savings.
Our mission is about more than just making medications. We’re working within, and striving to improve, the health system at large. We see the main challenges facing the industry as they relate to the mental health sector as separate but related pieces of the same issue. There is a huge need to better understand individual responses to novel mental health treatments that are validated through both appropriate biomarker analysis and an increase in the inclusion of diverse populations for which to develop new treatments.
Psychiatry, in particular, is an area long overdue for a paradigm shift. Unlike other therapeutic areas, there are currently no validated biomarkers for predicting, diagnosing, or assessing psychiatric treatments. We are working daily to address this disparity and hope to drive future innovation in this space. In addition to the need for a comprehensive set of psychiatric biomarkers, we must extend the diversity of the populations that we include in our trials evaluating new treatments, not only in mental health, but across the sector. There is a stark absence of differentiated treatments for diverse populations at present. A recent study from the University of Cincinnati has shown that two people receiving identical treatment for depression can have very different outcomes depending on their race, education level, and employment status. Although we have decades of evidence that gender, race, and other factors influence whether and how a patient is diagnosed and what treatment they receive, current treatment options for mental health largely remain a one-size fits all approach.
The cell and gene therapy revolution has begun, but clinical and regulatory roadblocks are preventing these treatments from quickly — and safely — reaching the hands of patients in a scalable manner. A handful of gene therapies have been approved for several orphan diseases, including Duchenne muscular dystrophy and sickle cell disease, and several approved cell therapies, such as chimeric antigen receptor (CAR)-T cell therapies, offer hope to cancer patients who have failed all other lines of treatment.
This is only the first wave of cell and gene therapies — the U.S. FDA expects the majority of new drug approvals to be in this space over the coming years. But to reach that explosive growth, cell and gene therapy developers need to overcome clinical delays and regulatory holds that have been plaguing the field. Effectively scaling up the manufacturing and clinical testing of these treatments will require clear industry and regulatory standards on quality and safety.
Regulators, doctors, and patients need more comprehensive assessments to be assured that dangerous clones or infectious agents are not making their way into patients, that cells are being modified and edited consistently, and that the resulting cells are fit for purpose. Single-cell characterization at every step of the drug development process — from early-stage research, through the clinic, and to manufacturing — can provide a clear picture of what’s been modified within a cell, and whether those changes could cause any health concerns in patients.
Genomics’ role in the life science vision “is only as credible as its implementation,” as Sir Jonathon Symonds commented in a Public Policy Project panel. The 2021 UK Public Policy Projects Genomics Revolution report goes on to say that “the diversity of genomic data must be improved to avoid the risk of health data poverty, and by extension, health inequalities.”
We agree that implementation matters. With the abundance of data now available to inform drug discovery and research decisions, our customers tell us that one of the biggest challenges that the industry is currently facing is what I like to refer to as “science friction.” Discovery and research productivity are seriously impeded by high-friction software tools and obstacles to data integration across both modalities and studies. This means that researchers are wrestling with the fundamentals of data storage, data formats, and data normalization, as well as grappling with different software packages and versions and struggling to run analytical tools at scale in a cost-effective way.
We applaud the many global initiatives to increase diversity in population studies like 54gene and DNA do Brasil. With more representative data pools, projects like these will provide the data foundation to drive more effective personalized medicine treatments that will cut health outcome inequalities.
As Professor John Quackenbush said: “technology is advancing at such a pace that today we can assemble datasets that give us a foothold in addressing questions that were unanswerable even two or three years ago.” Assembling new data sets addresses only half the challenge. Agile science platforms with integrative analytics and superior cloud economics are equally critical to reducing the science friction around leveraging data abundance and diversity.
With the continued, increased prevalence of biologics and ATMP compounds, pharma and biopharma organizations face the challenge of expanded regulatory scrutiny and complex supply chain management. Regulators are in a precarious position to ensure that proper checks and balances are in place to guarantee product integrity and safety without compromising innovation and the speed of development. A collaborative approach to addressing the challenges among both regulatory bodies and clinical development organizations will be paramount to success.
Inherently, more advanced therapeutic compounds come with more complex supply chain processes. Pharma organizations will need to manage supply extremely carefully, given that development costs continue to increase. It’s not unusual to see new drug batches with commercial values in the hundreds of millions of dollars. Ensuring accurate levels of supply to address patient forecasting and recruitment while staying within reasonable cost measures will be increasingly challenging. This is compounded by the difficult handling requirements of these compounds, such as cold and ultra-cold storage. In the current geopolitical climate, these difficulties are even more pronounced, with a reduced number of flights and shipping options, increased fuel costs, and overall inflation that is typically exceeding the standard producer price index (PPI). The challenge is not small, but success means bringing life-changing therapies to patients and changing millions of lives for the better.
Many industries have been adapting to digital transformation, and, for the pharma/biopharma space, it has become a necessity. The pandemic has forced most industries to evolve their remote or virtual work capabilities in order to maintain operations, creating a need for systems that didn’t exist before. From a technology perspective, companies need to find a way to get disparate data systems to communicate or at least speak a common language. When important patient information is missed because data systems are siloed, the result is incorrect or inaccurate care. To alleviate these challenges, companies are turning toward real-time data, which has been historically siloed across and within these disparate care settings. By breaking down the silos and adopting common languages like ICD and LOINC codes, the research community can gain access to real-world patient data in a way that becomes meaningful. Over the last two decades, organizations have collected a significant amount of real-world data on patient therapy and treatment information, including detailed outcomes that result from treatments. Couple that with Big Pharma's ability to digest this data, then focus research efforts on prevention and treatment, and you have a powerful combination. Having access to this data can accelerate innovation designed to protect the most vulnerable populations among us, ultimately improving care outcomes for all.
Viral vectors are a key bottleneck in ATMP manufacturing and a main driver of the high costs of these products, accounting for as much as 40% of the cost of goods for gene and adoptive cell therapies (APMHE 61629).
Enabling technologies and a platform approach can help to streamline the process, but the focus remains on trying to decrease the cost of the entire process. Enabling higher titers in scalable processes will help to overcome these challenges. For instance, innovative reagents can boost the yield and productivity of viral vector processes, and processes are currently being validated at the 500-, 1,000-, and 2,000-L scales.
Another challenge is the time it takes to obtain regulatory approval for viral vector–based gene-replacement therapies. It would be good practice for new therapeutic innovators to develop a high-titer scalable process with regulatory approval in mind. This means selecting suppliers that provide reagents, consumables, and equipment with robust regulatory packages so that, in the end, a high-yield process with easy regulatory acceptance has been developed.
The productivity of our industry R&D is declining; we spend more than $2 billion to bring each new medicine to patients, yet 90% of all clinical trials fail. If we can improve the efficiency of this process, we can bring better medicines to patients faster and more cheaply, creating a more sustainable R&D model.
At Recursion, we’re tackling this issue by reshaping the traditional pharma pipeline. In its ideal state, a drug discovery funnel would be shaped like the letter “T,” where a broad universe of possible therapeutics is narrowed immediately to the best candidate, which would advance through subsequent steps of the process quickly and with no attrition. Our Recursion OS has enabled us to identify low-viability programs earlier in the research cycle, spend 50–60% less per program from discovery to IND, and advance programs to a validated lead in one-third of the time compared with industry averages. We do this by leveraging our proprietary Maps of Biology to infer hundreds of billions of relationships between disease models and therapeutic candidates that go beyond hypothesized and therefore human-biased targets. We then validate and prioritize the most promising candidates early in the research process. Ultimately, we believe that this approach is allowing us to industrialize drug discovery with less bias, more speed, and more scale.
Improving the diversity of clinical trials is one of the biggest challenges that the industry faces today. The U.S. FDA has recognized this and recently released guidance encouraging pharmaceutical sponsors to develop plans to address discrepancies in enrollment from underrepresented ethnic populations in the United States. In our research, we've found that these discrepancies can appear at the earliest parts of clinical recruitment. For example, Black trial candidates are around 40% less likely to move into screening for a trial than white candidates, with the key difference emerging at the pre-screening to in-screening transition. To even start to address this inequality requires capturing and reporting demographic information early enough to effect change. This has historically been a significant challenge to the industry.
At Reify Health, we are leveraging StudyTeam and Care Access to meet patients where they are, understand their unique needs and backgrounds at the earliest stages of recruitment, and pinpoint the qualitative and quantitative reasons limiting underrepresented groups from full participation in clinical studies. Beyond providing visibility, we will develop tools and techniques to address these limitations, and understand which interventions are best suited for the unique needs of specific study.
Finally, just as many studies are global in nature, so are the challenges of addressing clinical diversity. It will take years of concerted, systemic effort, but I'm confident that by working together and marshaling our collective resources, we can ensure that everyone, regardless of background, can benefit from life-saving clinical research.
One of the biggest challenges faced by the industry is definitely the uncertainty in supply chains. Market-approved therapeutics, which are integral to patient healthcare, are obviously affected by this. However, this also affects products in development and in clinical studies and subsequently goes on to affect their "time to market." The scarcity of raw materials and long delivery times are challenging for all parties involved. This is one of the reasons why Rentschler Biopharma relies on a strong network and reliable partners to effectively reduce this risk.
The geopolitical landscape also plays a major role in this context. I am convinced that this can only be solved through a multi-level approach: a combination of fostering innovative solutions, with right-first-time precision, in a strong community. Thus, we can continue to offer premium solutions to our clients and high-quality therapeutics to patients.
Fast advancement of technology development in the biotherapeutics industry resulted in the birth of various drug modalities that are designed to work optimally for many diseases with high unmet needs. However, high quality management and good manufacturing control of recent emerging technologies are still the biggest challenges facing the industry.
Over the past decades, the biosimilar industry paved an important path for high quality management while innovating process science to improve the efficiency of process development. What we learned from biosimilar development can certainly help the biopharma industry find solutions for its manufacturing challenges.
IDC predicts in its Futurescape Worldwide Life Sciences 2022 Predictions that, by 2026, two-thirds of life sciences companies will adopt the intelligent lab of the future, leveraging digital transformation and integrating the Internet of Lab Things (IoLT).
There is a clear race within the pharma/biopharma industry, particularly within R&D, to use experiment data for purposes outside of its original experimental context. In its simplest form, if past experiments and their data were available in a frictionless manner, we could reduce the number of repeated experiments. If we could use historical formulation analysis data to predict the “sweet spot” for a new product formulation, this would again reduce the number of physical experiments required and reduce timelines. Digital twins of bioreactors and bioprocesses could also reduce development time.
To enable this level of data science, lab systems and data flows need to be integrated to a degree that is unprecedented. Applications for experimental design, compound registration, electronic lab notebooks (ELNs), laboratory information management systems (LIMSs), scientific data management systems (SDMSs), instrument systems, and even different sites and geographies need to be end-to-end integrated in such a way that the data they produce is highly cross-linked and available.
The challenge of removing silos and harmonizing data is not new, but the degree to which this digital transformation needs to be delivered will test many organizations over the coming years.
While the biopharma industry has proven adept at producing small molecule and biologic therapies that treat broad disease categories in large numbers of people, the next opportunity lies in new modalities. Because venturing into new modalities requires de-risking, it’s a space best suited for companies, like ours, with a distributed financial support model — at least until the field has been able to demonstrate development and successful commercialization.
Still, it’s not easy — microbiome as a field is innovating along three axes: new science, new modality, and new business model. It's challenging to get one, let alone all three, right. That’s what drew me to Seed: in contrast with single-technology, single-platform companies, our platform-based approach enables rapid, efficient advancement of microbial research from discovery to market. This approach, paired with a deep commitment to scientific excellence and rigor, is necessary to realize the future of the field.
We know that the microbiome is the primary interface between humans and the environment, and we’re beginning to understand how that environment drives disease development and progression — two factors that heavily influence how we develop personalized therapies and identify unique targets. Because each person’s unique microbiome can drive the development or progression of disease, there is potential to design interventions based on microbial makeup. With advancements in sequencing technologies, large multi-omics data sets, and novel computational techniques, we can also realize the potential of microbes — as both living medicines and probiotics — to modulate this ecology for key health outcomes.
The biggest challenge that the pharma and biopharma industries currently face is unwanted immunogenicity. Immunogenicity is the ability of a substance or antigen, such as a foreign or potentially dangerous protein, to provoke an antigen-specific immune response. Although immunogenicity is needed to defend the body, it can also result in unwanted immune responses to lifesaving therapies or to auto-antigens that can lead to autoimmune disease. Many strategies to address unwanted immunogenicity target downstream immune effectors and are not antigen-specific, resulting in broad immune suppression that introduces patients to significant risk of infection and other malignancies. We think that the key to overcoming this big challenge of unwanted immunogenicity is to specifically stop the immune cascade before it begins. Our ImmTOR® platform technology is designed to induce antigen-specific immune tolerance prior to the initiation of the immune cascade through communication of a tolerogenic message to antigen-presenting cells. This tolerogenic message results in an induction and expansion of antigen-specific T regulatory (Treg) cells and mitigation of an unwanted immune response. Our approach has broad applicability as showcased in our three focus areas: re-imaging immunotherapy for autoimmune disease, unlocking the potential of gene therapy, and amplifying the efficacy of biologic therapy. Through overcoming unwanted immunogenicity without broad immune suppression, the biotech and biopharma industry will be able to provide therapeutic solutions to patients without the serious side effects seen across these treatment landscapes today.
From the point of view of a primary packaging manufacturer, the biggest challenge to the pharma industry today is manufacturing operation disruption caused by the COVID-19 pandemic and compounded by the war in Ukraine. These events have significantly impacted global supply chains in terms of access to raw materials (including packaging components), and it is increasingly challenging to transport them from the supplier. Continuous labor shortages are driving productivity down and delaying necessary validation and qualification activities, further exasperating final drug product availability. Energy market increases have also impacted operating costs for suppliers in industries with a heavy dependence on energy, such as glass manufacturing. These factors combine to drive up supply chain and operating costs, causing back orders.
To mitigate these types of supply chain challenges, the industry is focusing more on the development and manufacturing of drug products and partnering with suppliers to take on more of the non-core activities. For example, we are seeing an acceleration towards the implementation of ready-to-use (RTU) primary packaging components as a preferred solution. Filling machine equipment manufacturers are also answering to this trend by providing more options to handle RTU and non-RTU components to allow for maximum flexibility for pharma companies. SGD Pharma’s Sterinity platform of molded glass vials has also been strengthened to offer sterile RTU vials to its customers and meet their demand for added services to be provided by suppliers.
One of the biggest challenges facing the biopharma industry is siloed and disconnected data at scale and not enough multimodal data (imaging–radiomic, genomic, proteomic, biologic, toxicity, structured, and unstructured clinical data) being leveraged to fully understand a patient’s profile in the context of other patients. When data is not siloed and all stakeholders can contribute and share various pieces of a biological puzzle, it can reveal the full spectrum of a disease for better drug development.
Another major challenge is overcoming the hurdles associated with clinical trials. These challenges include lack of testing globally to match patients to the right trials due to centralized approaches, slow recruitment of patients to trials, inability to follow patients longitudinally to fully understand their response to a particular drug, and the ability to develop and launch predictive algorithms developed in support of trials into clinical routine. Big data approaches are increasingly becoming vital to discover new treatments for diseases, to find the right patients, and to bring a product to market. But these challenges must be addressed in order to speed up the drug development process and focus on patient-centered care.
There are decades of infrastructure and business processes on which pharma executives make decisions, and which are likely not attuned to true innovation. Research and development groups are inherently innovative, investigating new science, exploring every option to bring new drugs to market, and requiring deep financial support to do so. Alternatively, a company’s commercial effort is based on structures, project decision rules, and budgets that adhere to what has been done in years past. Innovation happens when a company balances the drive toward drug discovery and commercial success across all aspects of the company, allowing innovation to pull through to the commercial teams and budgets.
Innovation can spark with one success in an unlikely place supported by one executive. I have seen lasting innovation happen in this way across my career. But pharma faces challenges from operational and discovery boundaries set by financial expectations. It would be wise for leaders to set a budget for a Tiger Team charged with investigating new ideas and proving collaborations that point to creative new directions.
Cancer remains a leading cause of death worldwide. Advancing therapeutics that can benefit the largest number of cancer patients and improve survival and quality of life remains a great challenge for our industry. Immune evasion has long been recognized as a limitation to using the body’s own defense system to fight cancer. The arrival of immune checkpoint inhibitors (ICIs) greatly expanded the cancer immunotherapy toolbox and transformed the treatment landscape. By targeting immune checkpoints, such as PD-(L)1, ICIs enhance T cell activation to kill tumors. Though ICIs have earned some notable clinical successes, the ongoing challenge is to develop combination agents with a strong synergistic, not just additive, effect with ICIs. Clinical data from combinations of ICIs with existing chemotherapy and targeted agents appears to be falling short. Novel approaches are needed.
We believe that this challenge is two-fold: achieve cancer control while also ensuring durable anti-cancer immunity for patients to not only survive but thrive. Our strategy has the potential to enhance immunotherapy by creating an optimal environment to achieve synthetic lethality and induce tumor necrosis, a type of immunogenic cell death that targets cancer cells, cancer stem cells, and tumor-associated macrophages, and also to convert the tumor microenvironment from immune-evasive to immune-responsive. Once the tumor microenvironment is primed, ICIs’ potency is amplified and further leads to T cell activation for tumor killing. We hope to see the industry continue to think outside the box and invest in creative strategies to enhance the effectiveness of immunotherapies and offer patients with difficult-to-treat cancers transformative treatment options.
When you ponder the myriad of market, environmental, and regulatory issues that have seemingly converged simultaneously, several challenges rise to the top. Supply disruptions related to sourcing, availability, and logistics continue unabated worldwide. From raw material manufacturing disruptions and transportation challenges to surging demand from biopharmaceutical manufacturers for critical ingredients, the pharmaceutical ingredient supply chain crunch has been significant and has mirrored those of many other markets, with increased prices and longer lead times for specialty ingredients and chemicals from many suppliers globally.
Looking closer at the biopharmaceutical industry, demand for innovative chemistries driven by COVID-19 and mRNA technologies remains very high. Suppliers and manufacturers are challenged to keep up with orders for materials such as bio buffers, amino acids, cell culture media, and other key chemistries. Many suppliers are receiving volume orders well above historical levels. Adding in the increased consumer demand for medical procedures that individuals may have placed on hold or producers formulating alternatives to prevent prevalent illnesses, we’re still witnessing a market asking for more than the current supply.
As resources are more limited and supply chain shortages continue, pharma and biopharma companies must innovate to meet demand. Increasingly, pharmaceutical manufacturers are turning to partners for innovation and technical support, supply chain guidance, and industry foresight on regulations, trends, and market dynamics. As an ally to pharmaceutical manufacturers, we come in with our supply chain foresight, global distribution network, and direct accessibility to raw materials from leading brands to support our customers and address the current challenges that they face.
In the pharmaceutical industry, it usually takes over 10 years and costs on average U.S. $1 billion to bring a new drug to the market. However, the COVID-19 pandemic over the last two years challenged this status quo, as the industry tries to speed up the development process and to supply new treatments for the fast-spreading infectious disease within less than two years and at affordable costs. Our industry has also been demonstrating its ability to act collaboratively and quickly. By offering a highly vetted and true one-stop discovery, development, and GMP manufacturing platform, we consistently reduced the standard timeline of CMC development activities from initiation of cell line development to investigational new drug (IND) filing from 24 months to 12 months, and then to nine months and six months in the past five years. Now with the COVID-19 pandemic, we achieved a record-breaking 2.5-month timeline for a number of anti-COVID-19 neutralizing monoclonal antibody (mAb) projects. In addition, timelines from IND to Emergency Use Authorization (EUA) or Biologics Licensing Application (BLA) have been dramatically reduced. Of significant note, in one example, a neutralizing mAb was developed from the start of cell line development activities to EUA within an unprecedented timeline of 14 months. Thousands of kilograms of this neutralizing mAb were manufactured within months for therapeutic applications across the globe. What the industry learned from the COVID-19 projects should be applied in the expedited development of other biologics for treatment of diseases such as cancers, autoimmune diseases, neural degeneration, and rare diseases. Going forward, the biggest challenges for biologics development remain in terms of achieving the fastest speed and lowest costs as possible. Patients don’t need to wait 10 years for a treatment or have to die of the disease due to the expensive drug development and manufacturing cost. More high-quality biologics would be available and affordable due to expedited timelines and widespread use of advanced enabling technology platforms.
The biopharmaceutical industry has fostered undeniable scientific and technical progress in the last decades, placing the sector on the cutting edge of innovation. However, there is one domain that the biopharma industry has paid only minimal attention to so far: ecology. Indeed, developing and operating a biopharmaceutical process requires massive amounts of raw materials and consumables; several thousand liters of raw materials like cell culture media, buffer, and cleaning solutions, together with an impressive amount of plastics, are necessary to produce one kilogram of biopharmaceutical product. Besides being detrimental to the environment, this also raises the question of supply and the associated risks of shortages. Sustainability is thus an outstanding challenge that the biopharmaceutical industry needs to face. This will require developing greener processes — i.e., consuming fewer resources and generating less waste. This will also require reducing the number of experimental trials necessary to develop a process. Part of the solution may lie in digital initiatives along three focus areas: (i) the structuration and standardization of experimental results in order to ensure data completeness and reusability; (ii) the implementation of predictive simulation to virtually test a wide range of process conditions; and (iii) the rational evaluation and comparison of various process scenarios based on well-defined criteria to select the most appropriate options.
Nice Insight, established in 2010, is the research division of That’s Nice, A Science Agency, providing data and analysis from proprietary annual surveys, custom primary qualitative and quantitative research as well as extensive secondary research. Current annual surveys include The Nice Insight Contract Development & Manufacturing (CDMO/CMO), Survey The Nice Insight Contract Research - Preclinical and Clinical (CRO) Survey, The Nice Insight Pharmaceutical Equipment Survey, and The Nice Insight Pharmaceutical Excipients Survey.