Computational Drug Discovery · AI/ML · Preclinical Strategy
Proton Scientific Consulting brings senior computational leadership to pharma and biotech programs — sharper go/no-go decisions, fewer wasted synthesis cycles, and chemistry that moves toward the clinic. From target assessment through IND-enabling studies, without the cost of building an internal team.
Led by Bryan D. Cox, Ph.D. — Founder & Principal
Career experience spans
Capabilities
Senior-level computational expertise, embedded directly in your discovery programs — without the overhead of building an internal platform team.
Docking and covalent docking, virtual screening, free energy perturbation (FEP), molecular dynamics, and quantum mechanics calculations to drive SAR and candidate selection with physical rigor.
Predictive and generative models built for real discovery decisions — not demos. Deep neural networks, active learning, and generative chemistry integrated with physics-based validation.
Private, secure LLM and retrieval-augmented generation (RAG) deployments, custom MCP servers, and AI agents with domain tools — so your scientists mine internal knowledge without exposing it.
Synthesis-informed library enumeration, proprietary screening library design, database mining, and compound prioritization grounded in medicinal chemistry tractability and IP strategy.
Acting as your senior computational voice: portfolio and program strategy, target druggability assessment, go/no-go framing, and clear communication to executives, boards, and scientific advisory boards.
Experience directing 6+ direct reports and 40+ CRO scientists across concurrent programs. Vendor selection, CRO management, resourcing, and scientific mentorship for growing computational teams.
How I work
Most computational scientists specialize in one method and fit every problem to it. I'm a generalist by design — fourteen years spanning physics-based simulation, machine learning, and generative AI means the method gets chosen to fit your problem, not the other way around.
Before any calculation: the target, the chemistry, the data you already have, and what success actually requires. The most sophisticated method in the world is wasted effort if it answers the wrong question.
Free energy perturbation when a congeneric series needs rigor. A predictive model when a million compounds need triage. An LLM agent when the answer is buried in your own literature. Each earns its place on some problems and fails on others — and the right answer is often a combination.
A result your chemists don't trust or your executives can't act on hasn't landed. Findings arrive as plain recommendations with confidence and caveats stated openly — ready for the bench, the boardroom, and the SAB.
Ways to work together
A defined question, a deliverable, a timeline — a virtual screening campaign, an FEP study on your lead series, a predictive model built on your data.
Your computational chemistry function, part-time: strategy, execution, and vendor oversight — senior leadership without the full-time hire.
A standing senior sounding board for program decisions, technical diligence, and board or SAB preparation.
About
Founder & Principal, Computational Drug Discovery
Bryan is a computational chemist and scientific leader with more than 14 years advancing small molecule programs from hit discovery through IND-enabling studies and into the clinic. His work has contributed directly to assets now in Phase I (oncology) and Phase II (virology) clinical trials.
He founded Proton Scientific Consulting in October 2025 after senior roles spanning AI-native biotech, precision diagnostics, and academic drug discovery — most recently as Senior Director of Computational Chemistry at Terremoto Biosciences, where he led computational strategy across programs reaching IND-enabling studies and Phase I.
His experience is deliberately cross-indication — immunology, oncology, hepatology, virology, and metabolic disease — with deep expertise in structure-based design, cheminformatics, and the practical application of AI/ML and generative models to real discovery problems.
Oct 2025 — Present
Proton Scientific Consulting
Computational chemistry and AI/ML advisory for pharmaceutical clients.
2022 — 2025
Terremoto Biosciences · Oncology
Computational strategy across discovery through preclinical; three programs to IND-enabling studies, one to Phase I.
2021 — 2022
Edifice Health · Immunology & Aging
AI/ML strategy, biomarker discovery, and predictive diagnostics.
2019 — 2021
Atomwise · AI/ML Discovery
Med-chem team lead across three programs; 12+ patent filings using the AtomNet platform.
2015 — 2019
Emory University School of Medicine · Virology
Structure-based antiviral discovery; HBV asset out-licensed, now in Phase II.
2012 — 2015
Emory University · Liotta Lab
Molecular modeling and structural NMR for HIV and oncology targets.
Get in touch
Whether you're assessing a new target, stuck on a series, or deciding how AI fits into your discovery workflow — let's talk about what you're working on.
Prefer email? Write to bryan@protonscientificconsulting.com
Proton Scientific Consulting
Atlanta, GA · Serving clients remotely