March 19, 2020 PAP-Q1-20-NI-009
A: The analytical characterization of biologics is driven by new technology development coupled with the industry’s growing experience. Over recent years, this has led to an interest in some analytical techniques, for instance, mass spectrometry, being employed both earlier in development and as part of lot release. Looking ahead, the industry will focus on data-rich techniques, such as mass spectrometry, to allow more critical quality attributes to be monitored in a single assay, improving process development. The increased throughput and data integrity that technological improvements have allowed have opened new parts of the manufacturing pipeline where complex analytical techniques can be deployed to drive insight and aid decision-making.
Additionally, if we again look at mass spectrometry as an example, hardware and software are becoming more user-friendly, and this helps to reduce the time taken by specialist operators to perform an assay. Biologics characterization involves a diverse set of advanced analytical techniques, and, as some technologies are maturing, there has been a move toward more automated sample preparation and data analysis to reduce timelines. If technology development continues in this direction, then this would make complex technology more accessible to more operators while potentially allowing a more rapid development timeline.
A: Technology that contributes to driving down overall cost of care for both healthcare providers and patients while simultaneously improving clinical outcomes will drive the industry forward over the coming decade. This will become especially important as healthcare costs continue to dominate U.S. elections and political discourse. However, this type of innovation must be supported by real-world clinical and economic data and also demonstrate value to patients and healthcare providers.
Right now, many hospitals are looking for avenues to remain profitable with the DRG payment system. For that reason, I anticipate a paradigm shift in hospitals looking to technology that expedites time to diagnosis and treatment. This could include technologies like AI and machine learning that support physicians in making clinical decisions and reduce the subjectivity of diagnosis. In the past few years alone, we have seen major advancements in the development of AI across multiple fields, including medical imaging.
New advancements will also include digital apps that assist administrators in automating tasks, as well as streamline the management and analysis of large healthcare databases. Leading technology will also include medical devices designed to enhance physician's efficiency to diagnose and treat patients without changing the clinical workflow or replacing standard of care.
As healthcare becomes more patient-centric, we can expect to see an advancement of technology that enables patients to better manage chronic diseases. We might see personal consumer mobile apps integrated with wearable technology that support patient engagement and adherence to medication and more accurately track health data. These interactive platforms could therefore continue to improve patients’ treatment experience and disease management, as well as enable healthcare providers to monitor patients remotely and customize treatments.
A: In the international contract services market, client relationships that have historically leaned toward a tactical nature will evolve into strategic relationships requiring the need for closely aligned strategic planning, capacity planning, and supply chain support and connectivity. As these strategic trends evolve, I foresee an emphasis on much more integrated systems, collaborative systems and services, and the need for near real-time data sharing and decision support tools. Couple these efforts with the overall regulatory emphasis on data integrity in general, I'd foresee the following technologies taking a front seat in Sharp's strategic platform across our international portfolio of companies.
EDC (electronic data capture) for all core/key packaging and business processes that will mine data in a real-time/near real-time environment, allowing for tighter customer collaboration and planning across the supply chain, including more visibility and collaborative communication during product launches. All systems and data exchanges will need to comply with all regional data integrity regulatory requirements, and, as such, infrastructure platforms will need to be virtualized and likely cloud-based with strict security requirements and high availability platforms. I would envision that only the top-tier service providers will be able to make such required investments, so I would see the competitive market changing and consolidating as a result of these enhancements.
I believe that serialization technology platforms will be leveraged to gain additional synergies and ROI above and beyond regulatory requirements (DSCSA and FMD for example). Companies will begin to integrate these platforms into systems providing layered security capabilities, as well as providing enhanced supply chain solutions (cold chain, frozen and specialty shipments) that will be more ubiquitous as products continue to become more complex, specialized, and personalized.
A: Over the next decade, better data management technology, AI, and machine learning (ML) are poised to make a big impact on the pharmaceutical industry and its contributions to innovation in R&D.
The effort required to get a drug approved for the market today is far more than that from 30 years ago, yet the recent string of impurity-related drug recalls from the FDA has increased the pressure to effectively and comprehensively manage the drug substance and drug product data life cycle before pharmaceuticals are circulated to patients. At a time when the amount of data that organizations are collecting is more disparate and greater in volume than ever before, being able to share data effectively and demonstrate data integrity are additional drivers for better data management. Dealing with complex data sets continues to be a major concern for researchers and pharmaceutical executives, so digitization efforts that help streamline workflows and help address this data management challenge will lead to an evolution in the technology stacks of pharmaceutical R&D. Effective, integrated data management technologies will accelerate organizations’ decision-making processes and maximize productivity by efficiently, and correctly, interpreting the data without the need for human intervention for every decision.
Integration of machine learning — and AI in general — is likely to grow over the next decade, by matching the power of human intelligence with intelligent technology. Machine learning will assist scientists in experimental design, relying on historical data from successful and unsuccessful experiments to provide guidance. This, too, will empower scientists to be more efficient in the laboratory, accelerating R&D in the pharmaceutical industry.
A: Throughout the 20s, cell-based therapies will rely on genome editing to increase the therapeutic mechanism of action. The engineering of cellular capabilities will include Boolean activation and control, giving therapeutic developers much greater control of elements such as cellular survival or persistence and safety, being activated only in the presence (or absence) of specific cellular signals. Cellular engineering will increasingly rely on improving reprogramming technologies, such as CRISPR/Cas and other nuclease or transposon systems affording much better sensitivity and specificity. Before the end of this decade, we will be thinking more and more about cellular circuitry as we historically thought about integrated circuits in computation, increasingly powerful and controllable.
A: We are seeing a rapid growth in in vivo gene therapy, with a number of therapies nearing late-stage readouts, and scalable manufacturing platforms will be key to ensuring sufficient commercial supply. New vectors, such as the ancestral AAV library being developed by Professor Vandenberghe from Mass. Eye and Ear, are designed to improve organ tropism and reduced immunogenicity, and Lonza has been involved in developing a scalable manufacturing platform for this new technology. It will also be interesting to watch what happens with the first allogeneic cell therapy approvals and the possibility for “off the shelf” CAR-T.
In the therapeutic proteins space, the next wave of ADCs, with their improved conjugation technology, as well as other complex formats, such as bispecifics and T cell engagers, could see strong growth in the next decade. Here, Lonza is investing in new molecular biology tools, including the piggyBacTM transposon technology and inducible promotors to stably express larger and more complex genes in a stable and scalable manner.
The microbiome remains fairly uncharted territory — the impact of modifying the balance of microorganisms is starting to be understood, and therapies harnessing anaerobic bacteria or phages have potential applications in oncology, metabolic disorders, and, excitingly, the central nervous system. Although many companies in this area are still early phases, the manufacturing requires very specific capabilities for both drug substance and drug product — the motivation for Lonza to form a joint venture with Danish company Chr. Hansen to offer cGMP manufacturing in this emerging field.
A: The future of the pharmaceutical industry will rely on the technology that drives it as healthcare shifts to being more digitized and patient-centric. Digital technologies, such as healthcare applications, medical crowdsourcing, and precision medicine, will shape the industry over the next decade.
Not only do healthcare applications help patients monitor all of their daily health data in near real-time, but it also strengthens patient–physician communication by allowing data to be easily shared so the doctor can help advise on broader health decisions and prevention. When patients have access to their own health information, they are more empowered to be engaged in self-care decisions to ultimately lead healthier lives. Healthcare applications also follow and support the patient in their health journey when a doctor is not present.
An estimated 25–30 million people are living with rare diseases in America that often lead to misdiagnosis or symptom management with no diagnosis at all. Medical crowdsourcing technology is helping physicians find a treatment path for patients through the collaboration of many medical minds. Getting a 360° view of medical perspectives and experiences from a wide range of backgrounds, specialties, and locations is the key to success. An example of this technology at work is Sermo’s Patient Cases capabilities, where physicians can crowdsource an answer within hours or days depending on the complexity.
The healthcare industry still approaches healthcare in a “one size fits all” approach by creating treatments and treatment plans to try and help everyone. Moving forward, we will need to use advanced technology to understand the individual disease biology of each patient to create the most helpful treatment based on personalized knowledge over generalized data. An example of the impact of personalized data can be seen in a recent Sermo survey of 515 U.S. physicians, which found that 53% believe highly personalized nutrition based on an individual’s genetics, metabolism, or microbiome will be available within 5–10 years.
A: In the next decade, leading technologies will come from collaborative clusters that bridge the challenges and shortcomings of the actual innovation process. The industry has started implementing digital technologies within companies’ operations. The next era will be the post-digital era, where data, genomics, analytics, and AI meet to address the needs and design of new business models.
From a therapeutic perspective, cell and gene therapies will be riding the biopharma wave in the next few years. The identification of new ways to deliver “healing” genes to targeted locations, like tumors or organs, will lead to personalized medicine. The personalized approach to therapies will be pushed by the application of big data analytics and outcome prediction. Furthermore, innovation in gene modification and large screening, powered by AI, offers the possibility to accelerate drug discovery and exploration of new indications, infusing speed and large scale to the process.
A: There is a strong consensus that digitalization will drive the pharma sector. It can be through various forms: artificial Intelligence/machine learning to more efficiently analyze results of clinical trials (as an example); use of wearable devices to track, in real-time, personalized critical health data; healthcare applications, and other forms of advanced data analytics (to improve R&D outputs, as an example). More specific to excipient solution suppliers like DuPont, we are seeing strong interest in improved manufacturability of drugs — like continuous manufacturing — as a way to reduce costs, speed the scale-up process, and increase the quality/reliability of the end drug. The pharma sector is clearly modernizing the way drugs are produced, and polymer suppliers play a key role in enabling this movement.
A: The newest developments in digital pathology, specifically the use of deep learning convolutional neural networks (CNNs) for digital image analysis (DIA) of scanned whole slide images (WSIs), promise to drive transformational advances in the 20s and beyond for a critical scientific field, toxicologic pathology. Toxicologic pathologists support the safety evaluation of chemicals, pharmaceuticals, and medical devices that are designed to improve human and animal health, protect workers, and ensure the safety of water and food supplies. As an industry, these specialized scientists are also committed to designing studies that reduce, refine, or replace laboratory animals (3Rs).
In 2019, Charles River, one of the largest companies working in this research area, evaluated over 4 million microscopic slides in support of the agrochemical, medical device, biotechnology, and pharmaceutical industries. DIA-driven studies using AI-CNNs are showing potential for improving quality, efficiency, and innovation and will result in dramatic effects on slide-based diagnostics in these gateway studies that support regulatory approvals by government agencies like the FDA and the Environmental Protection Agency (EPA). Additionally, DIA may reduce or refine the use of animals in research in support of global initiatives set forth by both the FDA and EPA, as well as regulatory agencies and other scientific organizations across the globe.
With the burgeoning commercial availability of user-friendly CNNs, scientists and toxicologic pathologists from all over the globe are collaborating with computer scientists focused on CNN development, validation, and application to regulated preclinical research. The momentum in general pathology and the toxicologic pathology field are exciting, and fueling this hub of innovation is early data. CNNs will potentially drive more objective, consistent quantification into the qualitative and descriptive science of pathology, speed data analysis supporting shorter development cycle times, decrease costs by more effectively utilizing pathologists, and advance animal model to human translation by identifying visual patterns that augment those captured by the toxicologic pathologists because of their specialized training and expertise. Toxicologic pathology is entering a digital renaissance in pathology sciences, and the 20s will be a key decade for further research and testing.
A: Over the coming decade, I believe that technologies in tissue engineering will continue to propel the biotech industry forward by harnessing the body’s natural ability to heal itself. Specifically, the expanded applications of regenerative medicine will continue to make an impact in a variety of ways.
Regenerative medicine is a modern, novel field where scientists are diligently working to expand on traditional drug development applications. Rather than simply addressing the comorbidities associated with a given disease, regenerative medicine has the potential to truly transform how we treat patients by leveraging the body’s innate ability to restore itself. As an industry, we are working to understand how to best use and process all types of human cells, from stem cells to amniotic tissue.
At Vivex, even though our facilities include one of the oldest tissue banks in the country, we are still working to implement the latest processing techniques and find new areas of research — 50 years of service later. We are discovering that regenerative medicine is extremely unique, because the same products can be used for the treatment of both diseases and injury. For example, viable allogeneic bone allografts that can be used for bone remodeling have the potential to treat victims of a traumatic spine injury, such as from a car crash, or those with deteriorated bones caused by cancer.
Moving forward, we will also see regenerative medicine used to develop improved, minimally invasive surgical interventions. These types of interventions are desirable for several reasons, including pain management, fear of infection, and recovery time. For example, patients with chronic lower back pain often put off surgical intervention and rely on OTC medications to manage their pain. One product we are advancing, VIA Disc, is made from bone-derived cells to support the osteogenic healing processes. Studies to date have shown that minimally invasive interventions that use regenerative medicine, like VIA Disc, have the potential for treating disease as an alternative to surgery. Therefore, as new applications continue to be discovered, we believe harnessing the innate powers and versatility of regenerative medicine will lead the industry in the coming decade.
A: Broadly speaking, I think that scalable enabling technologies that are cost effective and can create dosage forms for a broad audience of patients will lead the way over the next decade. This includes technologies such as nanomilling, which can be leveraged for multiple dosage forms and virtually all routes of administration projects and is relatively inexpensive. Similarly, the technology and materials in drug development will evolve and help to simplify complex formulation processes. Novel polymer excipients, for example, can create differentiated dosage forms and expedite the drug
development process, progressing quickly from preclinical proof-of-concept into clinical and commercial.
A: During the last decade, there was great progress made in the development of technologies that have enabled us to better understand key drivers of human health and disease. This includes high-throughput sequencing technologies and computational tools. These technologies have further driven the development of therapeutics tools, such as CRISPR or other gene editing technologies, to advance innovative gene and cell therapies, as well as personalized medicine.
I believe this technology will continue to accelerate the development of drugs that address rare diseases at the genetic defect level, which has remained largely understood and under explored. In addition to gene and cell therapies for rare diseases, what we have learned about the human genome will enable us to develop more personalized medicines for chronic diseases that affect larger patient populations, like diabetes and cardiovascular disease. Further development will also continue in the drug delivery space, through the advancements we have made in both formulating and stabilizing biologics and complex small molecules and connected delivery platforms, such as smart devices. Our AFINA soft mist inhaler is an example of this type of new technology that allows for the inhaled delivery of gentle mist biologic formulations via the lungs. This is an alternative and patient-friendly option for those who wish to avoid the hassle and pain of regular injections. With the reported increase in the incidence of many chronic diseases and problems of low adherence to medications, innovative technology that enhances effectiveness of medication and supports adherence, such as inhaled therapy, will impact the treatment landscape. This will provide patients with more drug delivery alternatives to choose from based on their preference and need.
A: In vitro bioequivalence for the development of generic inhaled pharmaceutical products continues to present the industry with significant and evolving challenges. Developing and performing suitable analytical strategies to satisfy evolving regulatory requirements while establishing a robust development process that ensures that the developed generic product is successful continues to highlight the limits of the traditional approaches to in vitro characterization.
Regulators are advancing the expectations for the content of in vitro testing programs through continued development of general and product-specific guidance, with an expectation for the inclusion of newer techniques, such as spray pattern/plume geometry testing for MDIs and a clearer focus on identifying and controlling critical quality attributes as an integral part of the overall development.
The traditional inhaled product performance tests of APSD and delivered dose have proven themselves to be vital tools in the development and testing of inhaled products and form the backbone of any inhaled product specification. However, while they can tell us information about how much drug is released and its size, it does not provide information on other factors, such as the nature of the deposition (e.g., individual particles, agglomerates, or co-deposited with a carrier or a second API particle) or the morphology of the particles themselves. Both are factors that will have an influence on the actual bioavailability and delivery of the drug locally and systemically. Many companies have now been in the position where in vitro work has delivered a strong and comprehensive data package showing good equivalence between the reference and generic products, only to see PK or PD in vivo data show unacceptable differences between the products. Clearly, we need more physiologically relevant data for our in vitro analysis, and, while standard APSD and delivered dose tests themselves are not accurate physiological models, they do provide a platform we can build on.
Several advanced techniques are now available that can provide useful input to both improve the ruggedness of the development program to further de-risk clinical studies, or to further bridge IV–IVC to strengthen in vitro data submissions with a view to potentially avoiding clinical work. These include more accurate inhalation flow profiles, optimized lung dissolution models to allow for the dissolution behavior of the delivered API, and the use of morphologically directed RamAn spectroscopy (MDRS), which combines optical microscopy, computerized particle measurement, and per-particle Raman spectroscopy to deliver information on the size, shape, and identity of individual particles. Looking ahead, these new analytical strategies should allow for the development of stronger in vivo data packages supporting both greater clinical success and the possibility of successful in vitro–only generic approvals.
A: The development and rapid advancement of massively parallel sequencing technologies and analytical tools was a major breakthrough for the industry over the 2000s. This technology provided vast volumes of genotypic and phenotypic data, leading to a better understanding of human diseases. A more recent breakthrough is the development of single-cell “omics” technologies, which allow for the sequencing of DNA, RNA, proteins, and epigenetic profiles of individual cells. This has driven the discovery of rare and previously unknown cells and molecules with significant therapeutic potential and previously unknown cellular states and cellular interactions.
In the 2020s, the industry will begin to wonder how anything was accomplished before single-cell genomics and other single-cell omic technologies became widespread, mainstream, and routine. In the same way that a handful of companies began to routinely sequence genomes in the 2010s, new companies will continue establishing leadership positions in single-cell technologies and their application to drug R&D. These new technologies will continue to advance over the coming decade and will integrate with machine learning and artificial intelligence platforms for even more breakthroughs in understanding and treating human diseases. Advancements will include comprehensive measurements that simultaneously analyze DNA, RNA, protein, and epigenetic profiles for modeling cell physiology and mechanisms of disease. The precision of comprehensive single-cell measurements will enable researchers to identify the single moment, and the single cell, from which a serious disease progresses. In particular, these new technologies will lead to a surge of understanding of the tumor microenvironment, an area that is still not fully understood.
Advancements in single-cell technologies will also dramatically increase the productivity and speed of molecule discovery, such as antibody discovery, and the creation of novel classes of therapeutics, including polyclonal T-cell receptor cell therapies. Together, these advancements will democratize a field that has yet only been available to a handful of big pharmaceutical companies with large budgets for robotic automation.
Ashleigh graduated with a B.Sc. in Analytical Chemistry (Huddersfield University, UK) and joined Zeneca as a Biotransformation Chemist followed by technical and operational management roles with AstraZeneca and Syngenta before joining Intertek. She has a background in mass spectrometry and two decades of experience as an operational/technical team leader and study director spanning the drug development process (including PK studies, API/product characterization, CMC analytics). She is responsible for strategic growth and technical direction of Intertek’s Centre of Excellence for Biologics.
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