{"id":7608,"date":"2025-06-02T23:15:38","date_gmt":"2025-06-02T23:15:38","guid":{"rendered":"https:\/\/careers.bms.com\/blog\/\/"},"modified":"2025-06-30T12:26:12","modified_gmt":"2025-06-30T12:26:12","slug":"how-bms-uses-ai-to-accelerate-drug-discovery-transform-patients-lives","status":"publish","type":"post","link":"https:\/\/careers.bms.com\/global-es\/blog\/how-bms-uses-ai-to-accelerate-drug-discovery-transform-patients-lives\/","title":{"rendered":"Fostering an Ecosystem of Innovation: Using AI to Accelerate Drug Discovery at BMS Cambridge Crossing"},"content":{"rendered":"

\u201cInnovating in the AI machine learning space to make a faster impact on patients\u2019 lives.\u201d<\/em><\/p>\n

\"Thomas
Thomas Struble, Senior Principal Scientist, Computational Sciences, BMS<\/figcaption><\/figure>\n

That\u2019s how Thomas Struble, Senior Principal Scientist, Computational Sciences, summarizes the focus of his work at BMS. He and Isha Verma, Principal Scientist, Cheminformatics, are both members of the New Leads in Computational Science team at our Cambridge Crossing site in Cambridge, Massachusetts, which is accelerating small molecule drug discovery using AI capabilities.<\/p>\n

Learn about the exciting work these two scientists are doing in this rapidly evolving field, and the career possibilities BMS offers for professionals with science and technology skills to turn cutting-edge research into real-world impact.<\/p>\n

From Computer Science to Cheminformatics<\/strong><\/p>\n

As an undergraduate, Isha worked as a lab scientist, but wanted to explore other avenues to accelerate drug discovery outside of the lab. She went on to earn a master\u2019s degree in computer science and held several data scientist roles before starting at BMS in 2022.<\/p>\n

\u201cWhat drew me to the field was the opportunity to tackle big challenges within pharma, which machine learning and AI are well suited for,\u201d she said. \u201cAnd collaborating with chemists and biologists to translate our work into practice shows we\u2019re really making a difference in the drug discovery process.\u201d<\/p>\n

A Chemist\u2019s Move Into Machine Learning<\/strong><\/p>\n

Thomas Struble\u2019s career journey began with a PhD in organic chemistry, where he developed an interest in using data to drive decision-making. That led to a postdoc at MIT, where he \u201cwas able to use [his] science expertise to help develop AI machine learning platforms for chemistry.\u201d<\/p>\n

Thomas then worked as a scientist in informatics and machine learning for several years in the pharmaceutical industry before joining BMS in 2023. \u201cMy team has a strong vision of how we approach machine learning: applying innovative technologies to early drug discovery to make a real impact on patients\u2019 lives. And this group is incredibly motivated and passionate about that vision,\u201d he said.<\/p>\n

Innovation Accelerating Impact<\/strong><\/p>\n

Both Isha and Thomas see the use of AI and machine learning as a way to continually push innovation in drug discovery.<\/p>\n

\"Isha
Isha Verma, Principal Scientist, Cheminformatics<\/figcaption><\/figure>\n

\u201cThere\u2019s no way we can make every single possible compound that exists\u2014there\u2019s a limited subset we can explore. But with AI, we can look through all the data and find meaningful patterns,\u201d Isha explained. \u201cWe can actually generate large sets of virtual molecules that chemists would have come up with themselves. And I think we\u2019re just scratching the surface of where we can go.\u201d<\/p>\n

As Thomas describes it, \u201cmachine learning has had a huge impact in letting us make decisions much faster, making our test cycles much shorter, and helping us focus on the molecules that have the most potential to affect diseases.\u201d<\/p>\n

\u201cSome of the therapeutics we\u2019re working on are for diseases that have no current treatment. So if we can use these technologies to get drugs in the pipeline more effectively, efficiently, and with higher quality, we can make a real difference to people who are suffering,\u201d Thomas said.<\/p>\n

Committed to Harnessing the Power of AI in R&D<\/strong><\/p>\n

At BMS, we use innovative technologies\u2014like machine learning\u2014to accelerate every aspect of our business in support of our mission to develop transformational medicines for patients.<\/p>\n

\u201cThe commitment from our leadership to exploring where we can push the needle in drug discovery makes me proud to work here,\u201d Isha noted.<\/p>\n

\u201cThe number of avenues where we apply machine learning to our pipeline is unique at BMS,\u201d said Thomas. \u201cThat fosters an ecosystem of practical innovation, where we’re pushing new technologies to improve the quality of medicines.\u201d<\/p>\n

“Buzzing With Science” in Cambridge<\/strong><\/p>\n

When asked about working in Cambridge, both Isha and Thomas describe a thriving scientific community.<\/p>\n

\u201cCambridge is just buzzing with science,\u201d said Isha. \u201cAnd at our site we have a diversity of functions, so if you want to learn more about a specific area, you can always find an expert in it. That makes working here really exciting.\u201d<\/p>\n

\u201cThis is a unique location for science\u2014you have some of the top universities in the country, every big pharma company is here, and there’s a great community of support in the area,\u201d said Thomas.<\/p>\n

An Open Mind and a Hunger for Knowledge<\/strong><\/p>\n

What advice would these two scientists offer people interested in a computational science career at BMS?<\/p>\n

For Isha, an open mindset and a hunger for knowledge are critical. \u201cBeyond the prerequisite skills for the role, it\u2019s most important to be learning constantly,\u201d she said. \u201cIn the AI space there are new technologies coming out continually, and you need to be able to keep up to speed and be open-minded to new techniques.\u201d<\/p>\n

\u201cAnd don’t be afraid to fail\u2014it\u2019s an opportunity to learn something,\u201d she added. \u201cBe persistent and follow your passion, because that\u2019s ultimately what will make you happy at work.\u201d<\/p>\n

Thomas suggests throwing out stereotypes about \u201cBig Pharma.\u201d \u201cSometimes job candidates have the perspective that a pharma company can be bureaucratic and slow-moving. I tell them we have to find a balance; we can’t rush and risk harming people. But by using computational methods, we can make our timelines shorter while also reducing risk. You\u2019ll have the space to do that at BMS,\u201d he said.<\/p>\n

Turning Cutting-Edge Research Into Real-World Impact<\/strong><\/p>\n

When asked what motivates them, Isha and Thomas both point to a common goal.<\/p>\n

\u201cWe\u2019re all driven by the fact that this could be something that actually transforms the lives of patients,\u201d said Isha.<\/p>\n

\u201cThe guiding light for everyone on my team is that what we’re doing impacts patients\u2014knowing that we are solving some of the hardest problems so we can make patients\u2019 lives better,\u201d said Thomas. \u201cWe\u2019re all united by the BMS mission of transforming patients’ lives through science.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

\u201cInnovating in the AI machine learning space to make a faster impact on patients\u2019 lives.\u201d That\u2019s how Thomas Struble, Senior Principal Scientist, Computational Sciences, summarizes the focus of his work at BMS. He and Isha Verma, Principal Scientist, Cheminformatics, are both members of the New Leads in Computational Science team at our Cambridge Crossing site […]<\/p>\n","protected":false},"author":5,"featured_media":7613,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[96],"tags":[103,118,124],"class_list":["post-7608","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-building-careers","tag-career-growth","tag-innovation","tag-research-and-development"],"yoast_head":"\nFostering an Ecosystem of Innovation: Using AI to Accelerate Drug Discovery at BMS Cambridge Crossing - BMS Careers<\/title>\n<meta name=\"description\" content=\"Discover how AI is helping accelerate drug discovery at BMS\u2014and meet the scientists behind the work. 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