Oscar Carrasco-Zevallos, PhD | AI in Life Sciences R&D

Dr. Oscar Carrasco-Zevallos

Director, Data Science and Digital Health @ Johnson and Johnson Innovative Medicine

Experience in AI strategy

Oscar has led AI strategic initiatives and product development across Fortune 50 (Johnson & Johnson) and VC-backed biotech (PathAI) companies, bringing a unique lens into the rapidly changing ecosystem of AI for life sciences. Oscar has expertise in AI product strategy, pharma-tech partnering, AI startup diligence, and validation and regulatory strategies. Oscar is also passionate about mentoring startups and participating in Accelerators and Incubators within the Cambridge / Boston community.

Prior research

Oscar holds a PhD in Biomedical Engineering and has conducted AI research in industry and academia, including at MIT and Duke. Collectively, Oscar’s research has produced 130+ articles and presentations in top-tier journals (eg Nature Medicine, Nature Comms) as well as technical and clinical conferences. Oscar’s experience includes AI/ML (computer vision, generative AI, foundational models) in biopharma R&D and diagnostics across multiple diseases (ONC, IMM, CVM, ophthalmology).

Boston, MA

Google

Scholar

Insights | Thoughts and analyses on the ever-changing AI ecosystem

Strategy

Technology

VC & start-ups

Business value of data in the era of AI foundation models

Under construction!

The transformative potential of multimodal AI in healthcare

Will OpenAI kill my start-up? A survival handbook

Opinions and content are my own and do not reflect the views of my employer.

Portfolio | Prior work using AI to accelerate medical product R&D

Drug Development

Medical Device Development

Discovery & Preclinical

Clinical Development

Prototyping

Clinical Studies

Clinical validation
Regulatory strategy & design control

Abstract digital data background. Wave with moving dots. Musical stream of sounds. 3D rendering.

Featured Case Studies

Target ID via transcriptomic analysis

Automated assessment of trial endpoints

ML pathology combined with RNAseq from trial samples revealed a prognostic gene expression signature that suggested new targets for future research.

An AI biomarker test was developed to accurately assess key trial endpoints. Retrospective analysis of trial data demonstrated AI’s superior sensitivity for detecting drug effect.

P henotypic analysis in animal models

Real-time image guided surgery

A scalable platform with foundational AI models enabled phenotypic quantitation across multiple imaging modalities in pre-clinical animal models. System was deployed for use by large x-functional team including non-AI experts.

A 3D imaging prototype was developed and deployed in >200 human eye surgeries, demonstrating superior real-time visualization and guidance of surgical maneuvers.

Notable Awards

2022 - J&J Innovation Medicine R&D SPARK Innovation Award for groundbreaking strategies and platforms, J&J
2021 - Invited plenary presentation at FNIH Biomarkers Consortium Metabolic Disorders Meeting, PathAI
2020 - Selected for “100 Inspiring Hispanic Scientists in America,” Cell Press, PathAI
2019 - 1st place, Harvard-MIT Case Competition, MIT
2018 - National Institutes of Health NRSA F32 Individual Postdoctoral Fellowship, MIT
2018 - Burroughs Wellcome Fund Postdoctoral Enrichment Program Award, MIT
2018 - Leadership Award for Outstanding Service, Duke University
2017 - MIT’s Rising Star in Biomedical, MIT
2012 - National Science Foundation Graduate Research Fellowship, Duke University
2012 - Ford Foundation Predoctoral Fellowship, Duke University
2011 - Best Undergraduate Honors Research Thesis, Texas A&M
2011 - Craig C. Brown Outstanding Senior Engineer Award, Texas A&M
2011 to current - 10+ awards and distinctions for research presented at leading medical and technical conferences

Press

2022 - Paige, Janssen team up to launch AI-powered bladder cancer test: Fierce Biotech
2021 - Acceptance of AI drug development tool into FDA biomarker qualification program: PR Newswire
2021 - Oral presentation on AI-based drug development tool: PR Newswire
2017 - Intraoperative Optical Coherence Tomography feature: Retina Today article

Select Publications and Presentations (from 130+)

J. Iyer, ... O. M. Carrasco-Zevallos, … A. H. Beck, “AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases,” Nature Medicine, 2024. Link to publication
A. J. Ramon, C. Parmar, O. M. Carrasco-Zevallos … K. Standish, “Development and real-time deployment of a histopathology-based deep learning algorithm for patient pre-screening in a targeted-therapy bladder cancer clinical trial,” Nature Communications, 2024. Link to publication
B. Lutnick, … O. M. Carrasco-Zevallos, S. S. F. Yip, “A user-friendly AI system for histopathology image analysis system to accelerate pharmaceutical R&D,” Journal of Pathology Informatics, 2023. Link to publication
J. Conway*, M. Pouryahya* … O. M. Carrasco-Zevallos … C. Chung, “Integration of Deep Learning-Based Histopathology with Transcriptomics Identifies Key Genes Associated with Fibrogenesis in Patients with Advanced NASH,” Cell Reports Medicine, 2023. *Authors contributed equally. Link to publication
M. Carrasco-Zevallos, … K. Wack, “AI-based histologic measurement of NASH (AIM-NASH): A drug development tool for assessing clinical trial endpoints,” EASL International Liver Congress, 2021. Oral presentation. Link to presentation
C. Shukla, O. M. Carrasco-Zevallos, …J. E. Gane, “Machine learning enables quantitative assessment of histopathologic signatures associated with ALT normalization in chronic hepatitis B patients treated with tenofovir disoproxil fumarate (TDF),” AASLD, Boston, USA, 2020. Plenary oral presentation. Link to presentation

Invited Talks (from 10+)

O. M. Carrasco-Zevallos, AI-enabled devices to accelerate drug development, Bioengineering Seminar Series, UIUC, 2022.
O. M. Carrasco-Zevallos*, Asha Mahesh*, ML-Enabled Biomarkers for Clinical Trials: A Framework for Productization and Deployment, Bio-IT World, Boston, MA 2022. *Co-presenters
O. M. Carrasco-Zevallos, “AI-based assessment of NASH histology for treatment monitoring and risk stratification,” FNIH Biomarkers Consortium Metabolic Disorders Meeting, Plenary Session, Webinar 2021.
O. M. Carrasco-Zevallos, “AI-powered computational pathology for liver diseases,” HBV Liver Forum – Intrahepatic Panel, The Forum for Collaborative Research, Webinar, 2020. Link to presentation

Coming soon!