Artifical Intelligence
Machine Learning
We are an multi-disciplinary team of computational and experimental scientists focused on shortening the traditional time-to-development for antiviral drugs by integrating artificial intelligence (AI) and machine learning (ML), high-performance computing (HPC), and high-throughput experimental screening into every step of the drug design process to identify novel viral targets and develop safe and effective antiviral therapeutics.
Felice C. Lightstone, Ph.D.
Principal Investigator
Don Francis
Lawrence Livermore National Laboratory
Group Leader
Associate Program Lead of Medical Countermeasures
My research uses cutting-edge, multi-scale, in silico simulations to tackle problems in biology. A wide range of computational biology and machine learning methods that employ LLNL’s high-performance computing resources are used to accelerate the design and development of new therapies.
Adam Godzik, Ph.D.
University of California, Riverside
Professor of Biomedical Sciences
My research combines insights from physics and biology to answer the questions about the relation between the protein sequence and it structure and function.
Sandia National Laboratories
Staff Scientist
Oscar Negrete, Ph.D.
Tess Brown
Sandia National Laboratories
Staff Scientist
My research uses a broad spectrum of cellular, molecular biology, functional genomics, and nanotechnologies to assist in the formulation of new countermeasures and diagnostics for emerging infectious disease pathogens. I will bring his experience in Nipah virus entry research.
Maurizio Pellecchia, Ph.D.
University of California, Riverside
Professor of Biomedical Sciences
Director, Center for Molecular and Translational Medicine
A central theme of my laboratory is the development of novel methodologies to tackle protein-protein interactions (PPIs) as targets for drug discovery, and to further advance our most promising agents into potential therapeutics.
Sandia National Laboratories
Staff Scientist
Rommie Amaro, Ph.D.
University of California, San Diego
Professor and Endowed Chair
Department of Chemistry and Biochemistry
My research is broadly concerned with the development and application of state-of-the-art computational methods to address outstanding questions in drug discovery and molecular-level biophysics.
Jonathan Allen, Ph.D.
Lawrence Livermore National Laboratory
Bioinformaticist
My research focuses on using machine learning and artificial intelligence to build models of the drugs' effectiveness and predict draggability.
Edmond Lau, Ph.D.
Lawrence Livermore National Laboratory
Computational Chemist
My research applies molecular dynamics, quantum mechanical calculations, and molecular docking to study biological systems, including small molecule inhibitor and antibody designs to inhibit SARS-CoV-2.
Brooke Harmon, Ph.D.
Sandia National Laboratories
Staff Scientist
My research is focused on rapidly identifying and engineering novel antibody-based therapeutics with enhanced immuno-protective characteristics and efficient tissue penetration to combat encephalitic alphaviruses and SARS-CoV-2
Kevin McLoughlin, Ph.D.
Lawrence Livermore National Laboratory
Computational Biologist
My research focuses on machine learning methods applied to computational drug discovery and drug safety with a strong background in experimental design and experimental data analysis.
Hyojin Kim, Ph.D.
Lawrence Livermore National Laboratory
Computer Scientist
My research interests are broad areas of computer vision, image understanding and machine learning, including application to drug discovery
Xiaohua Zhang, Ph.D.
My research interests include: (i) drug discovery and high-throughput drug screening C++ toolkit development; (ii) fragment- and structure-based drug design; (iii) high performance computing applied to computational chemistry; (iv) algorithm derivation and program engineering for molecular simulation.
Lawrence Livermore National Laboratory
Computational Chemist
Brian Bennion, Ph.D.
Lawrence Livermore National Laboratory
Computational Chemist
My research interests are in computational prediction and optimization of small molecules for the discovery of molecular therapeutics.
Adam Zemla, Ph.D.
Lawrence Livermore National Laboratory
Computer Scientist
My research interests lie in developing new computational methods and numerical evaluation schemes to help detect and extract biologically meaningful inferences from complex biological datasets.
Dina R. Weilhammer, Ph.D.
Lawrence Livermore National Laboratory
Biomedical Scientist
My research focuses on innate and adaptive immune responses to viruses of biodefense and public health concern, including SARS-CoV-2. I have developed in vitro and in vivo infection models, including select agent pathogens under A/BSL3 Tier one Select Agent containment.
Nicole Collette, Ph.D.
Lawrence Livermore National Laboratory
Biomedical Scientist
Director, Animal Care Facility
With over 20 years of hands-on, in vivo mouse experimentation. my research has been in a wide variety of areas, including forensics, toxicology, infectious disease diagnostics, pathogen evolution, and therapeutic development.
