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Provided by Bristol Myers Squibb

This content was written by the advertiser and edited by Studio/B to uphold The Boston Globe's content standards. The news and editorial departments of The Boston Globe had no role in its writing, production, or display.

The AI-fueled R&D revolution underway in Boston’s backyard

In the race to translate scientific discoveries into treatments, artificial intelligence has emerged as an indispensable accelerator of R&D, advancing the path between discoveries in the lab and patient care at the bedside.

The end-to-end drug discovery and development process is long and complex, and researchers in Greater Boston are learning just how invaluable the collaboration between man and machine can be in a medicine’s journey from lab to patient.  

Drug discovery and development faces a revolutionary change in pace. To raise up to its challenges, companies like Bristol Myers Squibb are combining artificial intelligence (AI) and machine learning (ML) with a humanistic research approach, bringing early discoveries to their full potential and increasing operational efficiencies later in development. 

Woman wearing protective glasses and lab coat looks at the computer screen of scientific research.

Addressing AI and ML’s use in medical research and development (R&D), Mariann Micsinai-Balan, vice president of data science at Bristol Myers Squibb in Cambridge, says, “We have a uniquely powerful combination of vast amounts of deeply curated multimodal data, cutting edge scientific expertise, and novel computational methods. This makes my job exciting because there is always something new emerging: a new science, a new insight, something that we haven’t dreamed about.” Micsinai-Balan works with the company’s Global Biometrics and Data Sciences team to explore state-of-the-art AI and ML methods and how they can be applied throughout the R&D journey.  


From the outset: AI and ML’s use in drug discovery 

Transformative scientific innovation begins with the drug discovery phase. For researchers at Bristol Myers Squibb, this involves the use of strong causal human biology — the application of human data like genetics — to form new hypotheses and build upon the current understanding of disease biology to identify potentially new “druggable” targets.

Performing this novel research with the assistance of AI helps researchers more swiftly discover new insights that will bring the right medicines to the right patients. For example, AI technologies can explore the potential of early discoveries with predictive models that learn from billions of potential therapeutic options for beneficial effect in humans. This provides the ability to generate on-demand protein structures with a computer, enabling researchers to rapidly test and optimize the design of small molecules and biologics tailored to disease targets.

To the clinic: AI and ML’s use in drug development

Drug discovery is only a first step along the pathway to scientific breakthroughs. In fact, most new therapeutic hypotheses fail to lead to new drug approvals. Only one in every 10 new medicines that enter clinical development will emerge as an approved therapy. Using AI and ML, researchers at Bristol Myers Squibb are reengineering drug development with the intention of doubling the possibility of success. Mindful use of the power of AI and ML allows for the accelerated discovery of hidden patterns and the ability to gain new insights from complex multimodal data; as such, this information can be harnessed to develop safer and more effective drugs more quickly.

Propelling the use of AI and ML in collaboration with neighbors in Boston and beyond

Greater Boston, long recognized as an innovation hub, is ripe for continued progress in both life sciences and technology. Research hospitals, key academic institutions, startup biotechnology companies, and biopharmaceuticals are all now neighbors to a growing number of AI and ML-focused organizations, making collaboration on this new tech frontier within an arm’s reach.

Bringing capabilities in AI and ML to the benches of scientists is a priority being met with Bristol Myers Squibb’s R&D facilities in Cambridge and research sites across the globe. “As we bring our teams together here in Cambridge — driven by our passion and our curiosity — our scientists have the opportunity to work across different functional areas to collaborate and drive the science,” says Emma Lees, PhD, senior vice president, head, Mechanisms of Cancer Resistance Thematic Research Center and Cambridge Site Head for BMS Cambridge. “The reverse translational work done here, using an improved understanding of human genetics coupled with artificial intelligence and machine learning technology, is key to unlocking new discoveries. This allows us to bring information back to biologists, chemists, and protein engineers in the lab to improve ongoing research efforts and inform future hypotheses that fuel our next wave of discovery and pipeline advances.”

This collaboration is complemented with a network of over 100 active collaborations — with partners in the Greater Boston area, the West Coast, and across the Atlantic in the European Union. Micsinai-Balan says, “I think our partners feel our passion for science, they feel that once we commit to an external partnership, we are in it for the long haul. AI startup companies ambitious in their fight against cancer partner with us so in the foreseeable future we can bring our dreams to fruition. And it’s not only about data and technology, but, mainly so, the power of people that will bring all the pieces of the puzzle together. We are one team, and the spirit of collaboration with our partners is key in that sense.”

One such collaboration with a local Massachusetts-based organization, for example, has helped accelerate the drug discovery process by generating a substantial database of proteomic data, or the study of proteins in biological systems. This partnership has generated profiles for tens of thousands of components in just a few years, uncovering the unique ways cancer grows from profiling data of real-world patients. Progress at this pace would be impossible without the use of predictive technology powered by Bristol Myers Squibb’s unique strengths in cancer research.


Empowering underrepresented groups and breaking down barriers with the help of AI

On the other end of the R&D journey, the power of AI and ML is being harnessed to accelerate the drug development process and improve accessibility in a way that has not been possible before. Researchers at Bristol Myers Squibb utilize a “3D” approach to guide clinical innovation, a combination of data, design, and digital technologies, to help build drug development programs that are faster, more targeted, and barrier breaking.

Clinical trials are a fundamental but lengthy part of drug development. The power of AI is accelerating them with high-powered computing environments. Virtual clinical trials can be conducted via computer simulations without running them in the physical world, reducing the burden on participating patients and massively accelerating trial planning.

AI and ML are also used to complement efforts to ensure diversity in clinical trials, which is critical to ensure research reflects the patient populations most impacted by a disease. Researchers can integrate simulated data from underrepresented patient populations when such data is not immediately available, which is used to better reflect the diversity of patient populations intended to receive treatment.  

Researcher with brown hair pulled back in a ponytail wearing lab goggles and working with a machine.

Researchers are also leveraging cloud computing to identify improved study designs. The traditional approach involves manual calculation of a sample size, generating around 10 options. Through the help of cloud computing, 10,000 study design options can be generated in minutes, facilitating the identification of trial designs that are faster and more efficient, potentially bringing medicines to patients sooner. 

From end to end, AI and ML can help drive informed clinical decision-making and better experiences for patients. But, while data is foundational to this work, it is how scientists use it that drives decisions and enables new discoveries and breakthroughs.

Ethical use of data, AI, and ML from end to end

“I can’t emphasize enough that there is always a human element to any AI solution. The goal of AI is not to dehumanize work but to elevate the human component with technology that is people-driven and patient-centric,” says Micsinai-Balan.

With proper consents and authorizations, scientists at Bristol Myers Squibb build upon extensive proprietary data from several sources including clinical trials. Through clinical studies, the company can gather information on the safety and efficacy of its medicines, as well as patients’ scans, images, and any biomarkers, or molecules that identify abnormal processes. Large real-world datasets can also be gathered from hospitals and other medical systems as well as public, open data sources where Bristol Myers Squibb can collect information from patients receiving similar medicines to the ones being tested in its clinical trials.

With the emergence of AI in medical research being so recent, the US government and global health authorities are only in the early stages of rolling out guidelines and regulations around its use, leaving a great deal of responsibility up to individual organizations.

Group of researchers sitting around a conference table looking at a chart on a big screen.

The World Health Organization recently released a publication listing key regulatory considerations on AI in medical research, including transparency and documentation, risk management, data validation, data quality, and privacy and data protection. 

As the outlook of AI and ML’s use in R&D is still unfolding, organizations like Bristol Myers Squibb are actively setting the standards for ethical practices when using predictive sciences to make clinical decisions.

Embracing the future: A new era of patient-centric innovation

The future of these next-generation tools is promising and evolving quickly. It’s necessary to keep up increased collaborative efforts among R&D, AI, and ML organizations so scientific breakthroughs can continue to be made safely, efficiently, and quickly in the name of patients.

“Collaborations in AI and ML are extraordinarily powerful, and I am a firm believer that they will move science forward and bring our drugs to our patients much faster. Patient centricity and passion are the uniting forces in solving a scientific problem,” says Micsinai-Balan.

Allied with AI and ML, a R&D revolution is gaining ground in Massachusetts and beyond that holds immense potential for scientific advancements. It promises to usher in a pioneering new era, accelerating the development of life-saving medicine, helping to ensure that patients receive the care they deserve. Together, Bristol Myers Squibb and its partners are shaping a future where drug discovery and development is revolutionized, one breakthrough at a time.


This content was written by the advertiser and edited by Studio/B to uphold The Boston Globe's content standards. The news and editorial departments of The Boston Globe had no role in its writing, production, or display.