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This session will give an understanding of what it takes to realize the vision of fully integrated and autonomous drug discovery, both from an AI and data generation perspective.

Author:

Melissa Landon

Head, Commercial & Business Development, AI & Automation
MilliporeSigma

Dr. Melissa (“Mel”) Landon leads Commercial and Business Development for AI and Automation at Millipore Sigma, the Life Science business of Merck KGaA. With 20 years of experience of building cutting edge platforms across pharma and tech, Mel’s current work focuses on scaling intelligent automation and AI solutions that bridge scientific innovation with commercial value. She brings to this role a cross-disciplinary background spanning life sciences, technology partnerships, and enterprise transformation. Prior to joining MilliporeSigma, Melissa served as Chief Strategy Officer at Cyclica, an AI-enabled tech bio company (acquired by Recursion in 2023). Melissa completed her PhD in Bioinformatics at Boston University and performed postdoctoral studies in biochemistry and X-ray crystallography at Brandeis University. 

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Melissa Landon

Head, Commercial & Business Development, AI & Automation
MilliporeSigma

Dr. Melissa (“Mel”) Landon leads Commercial and Business Development for AI and Automation at Millipore Sigma, the Life Science business of Merck KGaA. With 20 years of experience of building cutting edge platforms across pharma and tech, Mel’s current work focuses on scaling intelligent automation and AI solutions that bridge scientific innovation with commercial value. She brings to this role a cross-disciplinary background spanning life sciences, technology partnerships, and enterprise transformation. Prior to joining MilliporeSigma, Melissa served as Chief Strategy Officer at Cyclica, an AI-enabled tech bio company (acquired by Recursion in 2023). Melissa completed her PhD in Bioinformatics at Boston University and performed postdoctoral studies in biochemistry and X-ray crystallography at Brandeis University. 

AI’s potential in clinical research extends beyond scientific data to the operational information that underpins every trial. When harnessed effectively, this data reveals patterns in study design, site performance, and execution that can accelerate development and improve outcomes. This session explores how AI and operational insights can reshape the future of clinical research. 

Author:

Mike Eckrote

Senior Vice President of Strategic Solutions & Technology
Advarra

Mike Eckrote is Senior Vice President of Strategic Solutions & Technology at Advarra, where he leads efforts to advance innovative approaches to clinical research and development. He brings more than a decade of experience in real-world data, technology solutions, and clinical trial optimization, with leadership roles spanning HealthVerity, Medable, and Medidata Solutions. Throughout his career, Mike has specialized in applying AI/ML, real-world evidence, and data-driven strategies to improve trial design, site selection, and patient outcomes.

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Mike Eckrote

Senior Vice President of Strategic Solutions & Technology
Advarra

Mike Eckrote is Senior Vice President of Strategic Solutions & Technology at Advarra, where he leads efforts to advance innovative approaches to clinical research and development. He brings more than a decade of experience in real-world data, technology solutions, and clinical trial optimization, with leadership roles spanning HealthVerity, Medable, and Medidata Solutions. Throughout his career, Mike has specialized in applying AI/ML, real-world evidence, and data-driven strategies to improve trial design, site selection, and patient outcomes.

The promise of AI in pharma is hindered by fragmented R&D data silos and the infrastructure gap between cloud-native research and on-premise manufacturing. This session presents an architectural blueprint for a unified, hybrid data platform designed to bridge these divides, creating a seamless R&D-to-manufacturing continuum.

We will explore how to first connect R&D data into a powerful knowledge graph. Next, we detail how to compute on this unified data by securely deploying NVIDIA's advanced AI models as microservices within a sovereign cloud environment. Finally, we demonstrate how a true hybrid architecture can bridge the cloud-native lab to the factory floor, unifying CMC and manufacturing data for end-to-end optimization.

Author:

Rameez Chatni

Global Director, AI Solutions, Pharmaceutical & Life Sciences
Cloudera
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Rameez Chatni

Global Director, AI Solutions, Pharmaceutical & Life Sciences
Cloudera

At AIDDD 25, Dirk Van Hyfte and Holly Soutter will share insights on reprogramming the entire drug discovery process, presenting the HYFT® breakthrough that enables biology to "compute itself"—making complex biological connections explainable, accessible, and actionable for the first time. This session will explore: 

  • Reprogramming Discovery: How AI-native platforms are reshaping how scientists interact with biological data and design new therapies. 
  • The HYFT® Breakthrough: Unveiling a novel computational approach that decodes universal biosphere patterns, unlocking unprecedented discovery potential. 
  • The Frontier of Explainable AI in Biology: Transcending black-box models to deliver clarity, transparency, and trust in AI-powered biological research.

Author:

Dirk Van Hyfte MD, PhD

Chief Technology Officer,
MindWalk

Dirk Van Hyfte stands at the forefront of innovation where artificial intelligence and biology intersect. As Chief Technology Officer of MindWalk, a Bio-Native AI company, Dirk leads transformative research powered by patented HYFT® technology and the LensAI™ platform—cutting-edge tools that unify biological data for accelerated drug discovery and development.

 

With a degree in Medicine and specialization as a Psychiatrist from the prestigious University of Leuven in Belgium and a PhD in medical artificial intelligence from Nijmegen University, Dirk combines deep clinical knowledge with pioneering expertise in computational science. Dirk’s expertise extends beyond the realms of technology and business. His entrepreneurial vision is reflected in the creation of iKnow, a natural language processing platform acquired by InterSystems, a global data technology leader, in 2010.

 

Dirk’s leadership has positioned MindWalk as a driving force in explainable and scalable biological AI, moving the field toward an era where biology itself computes, learns, and reveals new therapeutic frontiers.

 

 

At AIDDD 25, Dirk Van Hyfte and Holly Soutter will share insights on reprogramming the entire drug discovery process, presenting the HYFT® breakthrough that enables biology to "compute itself"—making complex biological connections explainable, accessible, and actionable for the first time. This session will explore:

  • Reprogramming Discovery: How AI-native platforms are reshaping how scientists interact with biological data and design new therapies.
  • The HYFT® Breakthrough: Unveiling a novel computational approach that decodes universal biosphere patterns, unlocking unprecedented discovery potential.
  • The Frontier of Explainable AI in Biology: Transcending black-box models to deliver clarity, transparency, and trust in AI-powered biological research.
... read more

Dirk Van Hyfte MD, PhD

Chief Technology Officer,
MindWalk

Dirk Van Hyfte stands at the forefront of innovation where artificial intelligence and biology intersect. As Chief Technology Officer of MindWalk, a Bio-Native AI company, Dirk leads transformative research powered by patented HYFT® technology and the LensAI™ platform—cutting-edge tools that unify biological data for accelerated drug discovery and development.

 

With a degree in Medicine and specialization as a Psychiatrist from the prestigious University of Leuven in Belgium and a PhD in medical artificial intelligence from Nijmegen University, Dirk combines deep clinical knowledge with pioneering expertise in computational science. Dirk’s expertise extends beyond the realms of technology and business. His entrepreneurial vision is reflected in the creation of iKnow, a natural language processing platform acquired by InterSystems, a global data technology leader, in 2010.

 

Dirk’s leadership has positioned MindWalk as a driving force in explainable and scalable biological AI, moving the field toward an era where biology itself computes, learns, and reveals new therapeutic frontiers.

 

 

At AIDDD 25, Dirk Van Hyfte and Holly Soutter will share insights on reprogramming the entire drug discovery process, presenting the HYFT® breakthrough that enables biology to "compute itself"—making complex biological connections explainable, accessible, and actionable for the first time. This session will explore:

  • Reprogramming Discovery: How AI-native platforms are reshaping how scientists interact with biological data and design new therapies.
  • The HYFT® Breakthrough: Unveiling a novel computational approach that decodes universal biosphere patterns, unlocking unprecedented discovery potential.
  • The Frontier of Explainable AI in Biology: Transcending black-box models to deliver clarity, transparency, and trust in AI-powered biological research.

Author:

Holly Soutter

Director, Lead Discovery and Profiling
Broad Institute of MIT and Harvard

Former Director, Lead Discovery and Profiling, Center for the Development of Therapeutics, The Broad Institute of MIT and Harvard

 Dr. Holly Soutter is a visionary leader and driving force in the convergence of biotech, pharma, and artificial intelligence, leveraging over two decades of drug discovery expertise.  Holly's innovation lies in her ability to strategically unify structural biology, biochemistry, and biophysics with cutting-edge high-throughput screening to generate the high-quality data essential for fueling next-generation machine learning models.

She possesses a clear-eyed vision: that the future of drug discovery is AI-powered, but that success hinges on a "biology-first," hypothesis-driven approach to ML integration. This deep commitment ensures that the technology serves the science, accelerating the path to novel therapies.

 While at the Broad Institute, Holly built a legacy of collaboration, working directly with machine learning experts to seamlessly integrate AI tools into hit finding workflows. These pioneering, integrated systems have democratized small molecule discovery, making it accessible to academic researchers worldwide.  As the founding co-chair of the Machine Learning in Drug Discovery Symposium, she acts as a crucial nexus, fostering vital connections between experimentalists and ML scientists and attracting luminaries who are defining the next era of medicine.

 

At AIDDD 25, Dirk Van Hyfte and Holly Soutter will share insights on reprogramming the entire drug discovery process, presenting the HYFT® breakthrough that enables biology to "compute itself"—making complex biological connections explainable, accessible, and actionable for the first time. This session will explore: 

  • Reprogramming Discovery: How AI-native platforms are reshaping how scientists interact with biological data and design new therapies. 
  • The HYFT® Breakthrough: Unveiling a novel computational approach that decodes universal biosphere patterns, unlocking unprecedented discovery potential. 
  • The Frontier of Explainable AI in Biology: Transcending black-box models to deliver clarity, transparency, and trust in AI-powered biological research.
... read more

Holly Soutter

Director, Lead Discovery and Profiling
Broad Institute of MIT and Harvard

Former Director, Lead Discovery and Profiling, Center for the Development of Therapeutics, The Broad Institute of MIT and Harvard

 Dr. Holly Soutter is a visionary leader and driving force in the convergence of biotech, pharma, and artificial intelligence, leveraging over two decades of drug discovery expertise.  Holly's innovation lies in her ability to strategically unify structural biology, biochemistry, and biophysics with cutting-edge high-throughput screening to generate the high-quality data essential for fueling next-generation machine learning models.

She possesses a clear-eyed vision: that the future of drug discovery is AI-powered, but that success hinges on a "biology-first," hypothesis-driven approach to ML integration. This deep commitment ensures that the technology serves the science, accelerating the path to novel therapies.

 While at the Broad Institute, Holly built a legacy of collaboration, working directly with machine learning experts to seamlessly integrate AI tools into hit finding workflows. These pioneering, integrated systems have democratized small molecule discovery, making it accessible to academic researchers worldwide.  As the founding co-chair of the Machine Learning in Drug Discovery Symposium, she acts as a crucial nexus, fostering vital connections between experimentalists and ML scientists and attracting luminaries who are defining the next era of medicine.

 

At AIDDD 25, Dirk Van Hyfte and Holly Soutter will share insights on reprogramming the entire drug discovery process, presenting the HYFT® breakthrough that enables biology to "compute itself"—making complex biological connections explainable, accessible, and actionable for the first time. This session will explore: 

  • Reprogramming Discovery: How AI-native platforms are reshaping how scientists interact with biological data and design new therapies. 
  • The HYFT® Breakthrough: Unveiling a novel computational approach that decodes universal biosphere patterns, unlocking unprecedented discovery potential. 
  • The Frontier of Explainable AI in Biology: Transcending black-box models to deliver clarity, transparency, and trust in AI-powered biological research.
  • Learn about novel methods to generate large, bespoke high-resolution datasets in a matter of weeks instead of months.
  • Explore how high-throughput, high-resolution interaction kinetics can fine tune AI models resulting in more efficient workflows and improved therapeutic characteristics
  • Discover how kinetic datasets generated under multiple pH conditions can support the development of pH dependent binders for cancer therapies using AI.

Author:

Bharath Takulapalli, PhD

Founder & CEO
SPOC Biosciences

Bharath is inventor of multiple foundational life science technologies at the interface of nanotechnology, systems biology and ML/AI, to extract 100x more information from systems biology than currently possible. He conceived Sensor-integrated Proteome On Chip (SPOC) technology to bridge a big gap in proteomics space, to democratize high-throughput functional protein screening. SPOC is the first and only technology that enables production of 1000s of full-length folded proteins on 1.5 sq-cm biosensor chips, to simultaneously screen for qualitative, quantitative, and kinetic information on protein bindings/interactions in a single assay, at once. Bharath is also the inventor of FENT solid-state nanopore technology for 1000x faster DNA sequencing at 1/10th cost, being developed by iNanoBio Inc. He raised $18M private capital and secured about $8M from DARPA, NIH. Bharath’s vision is to achieve 90% disease preemption, which is to detect and intervene in pre-disease phases, to cure before full disease onset.

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Bharath Takulapalli, PhD

Founder & CEO
SPOC Biosciences

Bharath is inventor of multiple foundational life science technologies at the interface of nanotechnology, systems biology and ML/AI, to extract 100x more information from systems biology than currently possible. He conceived Sensor-integrated Proteome On Chip (SPOC) technology to bridge a big gap in proteomics space, to democratize high-throughput functional protein screening. SPOC is the first and only technology that enables production of 1000s of full-length folded proteins on 1.5 sq-cm biosensor chips, to simultaneously screen for qualitative, quantitative, and kinetic information on protein bindings/interactions in a single assay, at once. Bharath is also the inventor of FENT solid-state nanopore technology for 1000x faster DNA sequencing at 1/10th cost, being developed by iNanoBio Inc. He raised $18M private capital and secured about $8M from DARPA, NIH. Bharath’s vision is to achieve 90% disease preemption, which is to detect and intervene in pre-disease phases, to cure before full disease onset.

  • Integrating AI and decision science to design faster, smarter, lower-risk trials
  • • Using adaptive methods to boost efficiency and responsiveness in trial design
  • • Turning complex data into insights that accelerate timelines and improve outcomes

 

Author:

Tom Oliver

Head of Product
Faculty

Tom Oliver is Head of Product at Faculty, where he leads the strategy and roadmap for Faculty Frontier™, the company’s decision-intelligence platform that helps enterprises operationalize AI in day-to-day decisions. Tom partners with executives and cross functional teams, including product managers, engineers, data scientists, and designers, to discover, build, and scale products that solve real problems for technical and business users. He collaborates closely with Faculty’s leadership and with key stakeholders and clients across pharma, retail, consumer goods, and healthcare, turning complex challenges into measurable outcomes. Before joining Faculty, Tom held leadership positions at PwC, focusing on technology enabled transformation, operating model change, and enterprise technology selection and deployment. His public writing explores the future of work, AI ethics, and human centric design, asking how powerful systems can advance human flourishing, not only efficiency. He holds a degree from the University of Oxford.

... read more

Tom Oliver

Head of Product
Faculty

Tom Oliver is Head of Product at Faculty, where he leads the strategy and roadmap for Faculty Frontier™, the company’s decision-intelligence platform that helps enterprises operationalize AI in day-to-day decisions. Tom partners with executives and cross functional teams, including product managers, engineers, data scientists, and designers, to discover, build, and scale products that solve real problems for technical and business users. He collaborates closely with Faculty’s leadership and with key stakeholders and clients across pharma, retail, consumer goods, and healthcare, turning complex challenges into measurable outcomes. Before joining Faculty, Tom held leadership positions at PwC, focusing on technology enabled transformation, operating model change, and enterprise technology selection and deployment. His public writing explores the future of work, AI ethics, and human centric design, asking how powerful systems can advance human flourishing, not only efficiency. He holds a degree from the University of Oxford.

Author:

Tarun Walia

Senior Director, Decision Science
Novo Nordisk
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Tarun Walia

Senior Director, Decision Science
Novo Nordisk

Author:

Stephanie Vakaljan

Director of Trial Analytics and Decision Support
GSK
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Stephanie Vakaljan

Director of Trial Analytics and Decision Support
GSK
  • Learn how real-world data is transformed into structured, usable intelligence through PRISM (Patient Record Inference & Structuring Module), an AI-enabled engine that converts fragmented, multi-modal patient data into inference-ready patient journeys supporting scalable clinical insights and model validation.

  • Explore how Zephyr’s AI-enabled multi-modal models (AIM Suite) predict drug response and reconstruct gene expression from clinically available inputs, such as NGS data from commercial LDTs and whole-slide images, enabling retrospective and prospective evaluation of treatment predictions across oncologic therapeutic classes.

  • Discover how Zephyr’s AI-driven software accelerates co-development and clinical integration, enabling fine-tuned foundation models to embed directly into R&D workflows while supporting rapid clinical intelligence queries, cohorting, and data-driven decision-making.

Author:

Anshu Jain, MD

Chief Business and Clinical Officer
Zephyr AI

Dr. Anshu Jain is Zephyr AI’s Chief Business and Clinical Officer. A double board-certified radiation oncologist and clinical informatician, he leads business development, clinical strategy, medical affairs, and partner collaborations—translating Zephyr’s AI and large-scale real-world data into solutions that help biopharma and diagnostic partners advance precision medicine for patients. Prior to Zephyr, Dr. Jain served as Chief Medical Officer at Aster Insights.

Dr. Jain has authored peer-reviewed publications in Nature Communications, Journal of Clinical Oncology (JCO), and JCO Clinical Cancer Informatics, and has served as a principal investigator for early- and late-phase oncology trials. He has advised the FDA Office of the Commissioner and the Oncology Center of Excellence, and provided clinical leadership to large-scale data initiatives including the NCI SEER program.

He serves on the Board of Directors of the Community Oncology Alliance, the Board of Advisors for the Duke Cancer Institute, and is an Assistant Professor at the Yale School of Medicine.

Dr. Jain trained in internal medicine and radiation oncology at the Massachusetts General Hospital and Columbia New York Presbyterian Hospital. He earned his M.D. with Highest Distinction from the University of Kentucky College of Medicine and a degree in Economics from Duke University.

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Anshu Jain, MD

Chief Business and Clinical Officer
Zephyr AI

Dr. Anshu Jain is Zephyr AI’s Chief Business and Clinical Officer. A double board-certified radiation oncologist and clinical informatician, he leads business development, clinical strategy, medical affairs, and partner collaborations—translating Zephyr’s AI and large-scale real-world data into solutions that help biopharma and diagnostic partners advance precision medicine for patients. Prior to Zephyr, Dr. Jain served as Chief Medical Officer at Aster Insights.

Dr. Jain has authored peer-reviewed publications in Nature Communications, Journal of Clinical Oncology (JCO), and JCO Clinical Cancer Informatics, and has served as a principal investigator for early- and late-phase oncology trials. He has advised the FDA Office of the Commissioner and the Oncology Center of Excellence, and provided clinical leadership to large-scale data initiatives including the NCI SEER program.

He serves on the Board of Directors of the Community Oncology Alliance, the Board of Advisors for the Duke Cancer Institute, and is an Assistant Professor at the Yale School of Medicine.

Dr. Jain trained in internal medicine and radiation oncology at the Massachusetts General Hospital and Columbia New York Presbyterian Hospital. He earned his M.D. with Highest Distinction from the University of Kentucky College of Medicine and a degree in Economics from Duke University.

Data powers the engine of artificial intelligence (AI), but not all data is created equal. While software capabilities are rapidly accelerating, the biopharma industry still largely lacks the intelligent hardware needed to generate clean, contextualized, and high-quality data that AI and machine learning (ML) models require to deliver on their promise.

Explore how today’s in silico process development tools for bioreactor scaling and mechanistic modeling of chromatography can help you get it right the first time now, and why the next generation of intelligent hardware will be critical to unlocking the full potential of AI/ML in biopharma.

Author:

Tobias Hahn, PhD

R&D Director, GoSilico
Cytiva

Tobias Hahn is R&D Director of chromatography mechanistic modeling activities at Cytiva. As former co-founder and CEO of GoSilico, now part of Cytiva, Tobias is responsible for delivering simulation software and workflows for in silico process development. He received his undergraduate education in computational mathematics and technical physics in Karlsruhe and Stockholm, earning his PhD in chemical engineering from Karlsruhe Institute of Technology (KIT). During his doctoral studies, he utilized his background in mathematics and software engineering to create the simulation software now known as GoSilico™ chromatography modeling software.

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Tobias Hahn, PhD

R&D Director, GoSilico
Cytiva

Tobias Hahn is R&D Director of chromatography mechanistic modeling activities at Cytiva. As former co-founder and CEO of GoSilico, now part of Cytiva, Tobias is responsible for delivering simulation software and workflows for in silico process development. He received his undergraduate education in computational mathematics and technical physics in Karlsruhe and Stockholm, earning his PhD in chemical engineering from Karlsruhe Institute of Technology (KIT). During his doctoral studies, he utilized his background in mathematics and software engineering to create the simulation software now known as GoSilico™ chromatography modeling software.

Author:

Cilon Li

Sr. Director of Engineering, Digital Products Development
Cytiva

Cilon Li is a digital and IT executive with over 15 years of experience in healthcare and biopharma. He is a strategic leader with a proven track record in driving digital transformation across supply chain management, product management, and R&D. At Cytiva, Cilon drives the company’s digital strategy and expanding product portfolio, encompassing Internet of Things (IoT), data analytics, AI/ML, software as a service (SaaS) and enterprise applications to help customers progress their digital biomanufacturing journeys. 

... read more

Cilon Li

Sr. Director of Engineering, Digital Products Development
Cytiva

Cilon Li is a digital and IT executive with over 15 years of experience in healthcare and biopharma. He is a strategic leader with a proven track record in driving digital transformation across supply chain management, product management, and R&D. At Cytiva, Cilon drives the company’s digital strategy and expanding product portfolio, encompassing Internet of Things (IoT), data analytics, AI/ML, software as a service (SaaS) and enterprise applications to help customers progress their digital biomanufacturing journeys.