Dr. Ana Solaguren-Beascoa is an Associate Director of AI with 10 years of experience in the field of AI. She holds a PhD in Theoretical Particle Physics. 

 
During her eight years in London, she built her career across multiple companies as an ML scientist, starting her journey in the biotech industry at BenevolentAI and later on at CoSyne therapeutics. Since, she has been working on projects such as LLM-graph enhanced models for target identification, protein druggability assessment, single cell RNA-seq foundation models or AI agents for rare diseases drug identification. Alongside the industry she was also a visiting lecturer at City University of London teaching machine learning and data science. 
 
Outside of work, she enjoys cooking and travelling whenever she gets the chance.

Bovornpat Suriyapakorn is a Quantitative Pharmacologist at Sanofi with a background in clinical pharmacy and biostatistics. Originally from Thailand, he previously worked as a lecturer and clinical pharmacist at Chulalongkorn University before completing his PhD in Experimental and Clinical Pharmacology at the University of Minnesota. His scientific interests include population PK, PK/PD, mechanistic and translational modeling, clinical trial simulation, and model-informed drug development, with particular interests in CNS drug development and biologics. Beyond his scientific work, Bovornpat is actively involved in the International Society of Pharmacometrics (ISoP), with a strong interest in education, mentoring, and scientific communication.

Stacey Tannenbaum, PhD, FISoP is a scientist and leader in Model Informed Drug Development, and principal at SJTPharm LLC. She is currently a Consultant and Coach to the MIDD community, supporting the development of leadership, communication, and change management skills.

Her previous roles include VP of Scientific Engagement at Metrum Research Group, and Pharmacometrics science and leadership at Novartis and Astellas. Stacey earned a BSE in Biomedical Engineering (Duke University), a PhD in Pharmaceutical Sciences and Applied Mathematics (University of Arizona), and a post-doctoral fellowship at the Center for Drug Development Science (Georgetown University). During her 25+ years as a PKPD scientist in Pharma and consulting, Stacey contributed to multiple drug development programs and successful submissions. Some of the outcomes of her work were optimization of dosing for future trials and labels, prediction of efficacy and safety with confidence, design of smarter studies and identification of key covariates, and bridging across populations, such as from healthy subjects to patients, and adults to children. As she transitioned from individual contributor into leadership roles, her expertise expanded beyond the science itself to include: championing science communication and soft skills development within technical teams, building infrastructure and implementing best practices for efficient and reproducible MIDD, guiding partners in translating clinical needs into strategic and model-informed solutions, and mentoring and training the next generation of leaders.

Stacey has had a significant impact on the global Pharmacometrics community. She co-founded ISoP, serving as its first President, and is an ISoP Fellow and Leadership Award recipient. Stacey co-founded the ACoP and was conference chair for the first three events; she remains an active volunteer in both ISoP and ACoP. She is the Executive Committee chair for WCoP, and is the chair of the Quantitative Pharmacology Network at ASCPT. She served as a board member of AAPS, chaired the AAPS M&S Focus Group, and was the co-chair for the AAPS Forum for Connecting Predictive Modelers. Stacey also co-founded the networking group Modeling and Simulation Applications in Clinical Pharmacotherapy (MoSAiC), now ISoP-NJ/NY/PA.

Dr. Akshanth Polepally is a Research Fellow and Director at AbbVie with over 15 years of experience in drug discovery, clinical pharmacology, and model-informed drug development (MIDD). At AbbVie, he leads efforts in optimal dose selection and the design and execution of clinical pharmacokinetic and pharmacology studies. He has contributed to multiple successful drug approvals and plays a key role in advancing dose optimization strategies across clinical development programs.

Dr. Benjamin Engelhardt is an Associate Director in Pharmacometrics at AbbVie. Over his nine years at AbbVie, he has led the oncology pharmacometrics team and contributed to multiple successful regulatory submissions, applying methods ranging from exposure-response analyses to advanced model-informed drug development. Beyond industry, he is a lecturer at multiple universities, a reviewer for journals including CPT and Nature, and a regular contributor to major scientific conferences and consortia.

Mark Chaplain is the Gregory Chair of Applied Mathematics at the University of St. Andrews. He received his Ph.D. in mathematics from the University of Dundee in 1990 and has been actively working mathematical biology with an emphasis on oncology since then. During this time he has published over 300 research articles and books. 

Additional details can be found at:
https://research-portal.st-and...

Alexander is a postdoctoral researcher and university lecturer working at the intersection of AI and Health at the AmsterdamUMC and ErasmusMC. He is also a use-case leader in the PHEMS consortium, an EU Horizon project that is developing the "Paediatric Health Data Space". This platform utilizes federated learning to enable partners to train ML methods using health record data obtained from all participating centres; all while maintaining strict patient privacy.

His past research has focussed on causal inference, generative AI, and bringing reliable AI methods to pharmacometrics. His current research focus is on de novo drug design, where he is working on fast-tracking in silico design candidates for experimental validation. He is the author of the Deep Compartment Models Julia package, which is an open-source project that provides a flexible environment to define and train novel ML-based models such as NeuralODEs within pharmacometrics.

Moustafa M. A. Ibrahim obtained his Ph.D. in Pharmacometrics from Uppsala University, Sweden. Following his Ph.D., Moustafa joined Pharmetheus AB as MIDD Consultant, where he provided pharmacometrics expertise across the spectrum of drug development, from non-clinical studies through late-stage clinical development and regulatory submissions. In 2024, Moustafa joined the Clinical Pharmacology and Safety Sciences Department at AstraZeneca, within the Rare Disease Unit, as a Global Clinical Pharmacology Lead. In this role, he provides scientific and strategic leadership for multiple global development programs to inform dose selection, optimize study design, support regulatory interactions, and enable data-driven decision-making throughout clinical development.

Martin obtained his PhD in Pharmacometrics from Uppsala University. He has 20+ years of drug development experience in areas such as metabolic disorders, autoimmune disease, infectious disease, hematological disorders etc. In 2012 Martin co-founded the consulting company Pharmetheus AB. In the consultant role he has been engaged as strategic advisor on behalf of multiple clients and acted as the main responsible consultant for 50+ pharmacometric data analysis projects on behalf of more than 20 different clients. The projects have ranged from pre-clinical translational projects to submission ready large-scale phase III PKPD analysis. These analyses have among other things contributed to 5+ successful NDA filings. 

Weidong Chen is an Associate Director in Data Science within Translational Medicine & Clinical Pharmacology at Bristol Myers Squibb. Since joining BMS in 2015, he has provided data science and programming leadership for pharmacometric analyses supporting early drug development, late-stage submissions, regulatory filings, and internal decision-making across Immuno-Oncology, Immunology, and Cardiovascular studies. Weidong brings deep expertise in SAS programming and clinical trial data standardization. Earlier in his career, he held statistical and SAS programming roles at Frontage Labs and Allergan, supporting Phase I/II, Phase IV, and bioequivalence clinical trials across multiple therapeutic areas. He holds a PhD in Biochemistry and Molecular Biology from Stony Brook University.

Amir Molavi is a Senior Software Engineer and Computational Scientist on the Data Science team at Bristol Myers Squibb in Cambridge, MA, where he supports AI, generative AI, and machine learning efforts within TMCP. His work focuses on bringing modern AI capabilities into scientific and data-driven workflows. Amir has a strong foundation in computer programming, physics, and mathematics, with deep expertise in Python, numerical modeling, and machine learning. Before joining BMS, he spent four years at Applied BioMath, where he redesigned the backend and Python client API powering model-informed drug discovery simulations. He previously conducted computational research as a postdoctoral associate at Northeastern University. Amir holds a PhD in Structural Engineering and an MSc in Applied Mathematics from the University of Akron, along with certifications in Machine Learning and Deep Learning from the University of Texas at Austin.

Tu Mai is a Senior Principal Scientist in Clinical Pharmacology, Modeling & Simulation at Genentech, where she leads clinical pharmacology and modeling and simulation strategies across multiple early and late-stage development programs. She has extensive experience in model-informed drug development (MIDD), including population PK/PD modeling, Bayesian forecasting, exposure-response analysis, and MIDD strategies to support regulatory submissions and dose optimization. Her work spans ophthalmology, oncology, immunology in small molecules and biologics. Tu received her Ph.D. in Pharmacology from Vanderbilt University.

Gina Song is a Director in the Oncology Global Clinical Development organization, Quantitative Pharmacology and Pharmacometrics (QP2) function at Merck. She has over 10 years of experiences in the Pharmaceutical industry across therapeutic areas including preclinical and clinical oncology, infectious disease and pediatric development for different modalities with time spent at Hamner Institute, Labcorp and currently Merck.  She is currently leading SC pembrolizumab program for clinical pharmacology and modeling &simulation efforts across indications as well as supporting regulatory submissions in global markets.

Mallika Lala is Senior Director, Group Leader at Merck in the Oncology Global Clinical Development organization, Quantitative Pharmacology and Pharmacometrics function. She has 15 years of drug development experience across therapeutic modalities, including early and late clinical oncology, infectious diseases and CV-met. She has been involved with the clinical development of pembrolizumab across indications and regulatory submissions in several global markets, most recently MIDD for dosing regimen and SC formulation additions, as well as multiple oncology assets including ADCs and targeted therapies. Before joining Merck, in industry in India to advancing pharmacometrics and was an ORISE fellow at FDA with focus on application of innovative quantitative approaches to enhance pediatric drug development.

• PhD biostatistics leader with over 18 years of research and development experience in biopharmaceutical industry, in various roles with increasing responsibilities.

• Passionate for complex problem solving and integration of different fields and functions across the biopharmaceutical development continuum.

• Strategic and managerial experience of teams of statisticians and programmers to support multiple programs/indications of various complexity.

• Out-of-the-box thinker and reliable team player with excellent stakeholder management, communication, analytical, computational and technical writing skills.

• Lifelong learner and entrepreneur with original research and publications on adaptive designs for clinical research. 

• Hands on statistical modeling, complex data analysis and simulations; proficiency in SAS and R; very good knowledge of the regulatory landscape.