President, Commercial Operations, Thermo Fisher Scientific, Pharma Services
A: We are at a pivotal time in the pharmaceutical industry — advancing technologies, including the use of advanced analytics and artificial intelligence are transforming the development and manufacturing of new medicines. Analytics, using the enormous data sets generated by drug development, are being used to develop systems that have the potential to predict the properties of new drug candidates.
Artificial intelligence is already in use in the practice of medicine — improving the speed and accuracy of diagnosing cancers and cardiovascular disease. Getting to an accurate diagnosis sooner will lead to patients receiving treatment earlier. And earlier diagnosis often leads to better outcomes.
We are utilizing the wealth of data we have collected over the years to get smarter and enable a better customer experience. We are using our data to identify trends and anticipate the needs of our customers.
Over the next 10 years, we will see an incredible transformation in the life sciences industry, leading to greater speed and accuracy in diagnoses, more personalized treatment plans/interventions — focused on prevention, early inter-vention and cures.
Andreas Persidis, Ph.D.
Co-founder and CEO, Biovista Inc. & President, Hellenic BioCluster
A: AI is poised to play an increasingly important role, as the pharmaceutical industry understands itself more and more as a data- and knowledge-intensive enterprise — and as it engages in the full “healthcare package” of prevention, diagnosis, personalized treatment and maintenance.
Through tools such as data mining and machine learning, AI will allow the industry to identify patterns and extract understanding and value from the massive amounts of data being generated. Effectively, AI will impact the scientific discovery paradigm of observation, hypothesis generation, testing and knowledge codification. What used to take multiple years will, in the future, take months, while covering much more of the “search space” than was previously possible.
AI will also help the industry understand and better leverage what it already knows. While our collective knowledge of biology is being generated and shared in a highly distributed and fragmented manner by academic laboratories and scientific journals, human biology is an integrated, self-contained system that exists independently of our understanding of it. AI, including its Augmented Intelligence flavor, will be instrumental in bridging this gap, by allowing researchers to know what is known and then to identify non-obvious connections that can generate new questions, new hypotheses and ultimately new treatments.
Data and knowledge integration will also lead to the creation of new value chains, catalyzing the restructuring of the broader industry. Finally, itself being subject to transparency demands, AI will impact corporate decision-making processes as well as organizational structures.
Chief Digital Officer, GE Healthcare Life Sciences
A: We believe that artificial intelligence (AI) and machine learning will play an increasingly important role in the diagnosis and prediction of disease — and will eventually become part of routine practice.
AI has already been used to support physician decision-making in the reads of CT, X-ray and ultrasound scans. Examples include the detection and diagnosis of suspicious lesions and nodules in lung cancer, which allow physicians to diagnose and give early treatments with greater certainty — without the need for tissue biopsy testing. AI algorithms have also been used to prognose skin cancer, allowing physicians and drug developers to intervene surgically and pharmacologically much earlier than previously. Also, treatment plans and monitoring are improving with AI-driven wearables and sensors.
One recent example is our partnership with Vanderbilt University Medical Center, which focuses on supporting safer, more precise immunotherapy cancer treatments. We will be developing diagnostic tools, including AI-powered applications, enabling identification of appropriate patients for clinical trials and treatment, reducing unnecessary and expensive trial failures and speeding up immunotherapy approvals. We will be analyzing and correlating the immunotherapy treatment response of thousands of Vanderbilt cancer patients with their anonymized health, demographic, genomic, tumor, cellular, proteomic and imaging data. After that, we will be developing AI-powered apps that draw on this data.
CEO, SEQENS North America CDMO (previously PCI Synthesis)
A: AI and robotics will help with analytics. The science we help clients with is getting increasingly complex, which means that the demand for increasingly sophisticated equipment, technology and training will continue to be important. We’re constantly evaluating new equipment and approaches to see if they can handle the complexity, speed up processes and reduce overall costs.
Artificial intelligence is already playing an important role in healthcare IT apps, and it will eventually play a significant role in diagnostics. AI is helping with clinical trials, predicting whether or not a trial will enroll on time. But it’s not yet sorting through patient data to provide insights that will help develop new drugs faster, more efficiently and with more efficacy.
In the shorter term, we’re seeing inroads of another type of advanced technology. Already, in our business, robots are helping with analytics. We have robotic arms helping with auto-sampling. We set up the sequence, and the robotic arms can do their job for however many hours, consistently, without getting distracted or making a mistake. We still need human analysts to draw conclusions and approve the quality. At some point, AI may be able to make things easier for human analysts — that moment isn’t around the corner, but we’ll be ready when it is.