Practice

Advisory work at the intersection of chemistry, programs, and decisions.

Most AI discovery platforms do not fail on models. They fail on whether the compounds are makeable, the SAR is real, and the next analog is worth synthesizing.

Drug discovery strategy

Target assessment, hit identification, hit-to-lead, lead optimization, candidate selection, and preclinical strategy.

  • Go / no-go framing for early programs
  • Progression criteria that chemistry and biology can share
  • Portfolio prioritization for lean teams

Medicinal chemistry

Compound design, SAR analysis, synthetic feasibility, physicochemical property optimization, and ADME/DMPK interpretation.

  • Design hypotheses that can actually be made
  • Property and liability triage before the next analog cycle
  • Synthetic strategy and troubleshooting

Computational drug discovery

Structure-based design, virtual screening, docking, FEP, ligand-based design, and AI/ML-enabled compound prioritization.

  • Integrating modeling with medicinal-chemistry decisions
  • Hit-finding campaigns that respect synthetic reality
  • Prioritization that a chemist will stand behind

AI & scientific evaluation

Chemistry-domain LLM evaluation, prompt and task design, rubric development, scientific fact-checking, and model-output review.

  • Benchmarking chemistry models against real discovery work
  • SAR, mechanism, and feasibility review of generated output
  • Practical limits of AI inside a live program

Pharmaceutical IP & technical support

Patent technical analysis, litigation support, composition-of-matter strategy, formulation/IP portfolio support, and scientific evidence review.

  • Claim construction grounded in the chemistry
  • Enablement, written description, and novelty questions
  • Teaching materials for counsel and fact-finders

Scientific advisory & due diligence

Technology assessment, AI drug-discovery platform evaluation, scientific diligence, R&D strategy, and CRO/vendor review.

  • Independent read on scientific robustness and differentiation
  • Reproducibility and feasibility questions investors actually need
  • Written diligence suitable for investment committees

Scientific advisory & R&D operations

Fractional leadership, laboratory strategy, technology implementation, external research management, and research infrastructure.

  • Interim medicinal chemistry leadership for early teams
  • CRO selection and external chemistry management
  • Experimental priorities when resources are finite

Compound design & synthesis

Route planning, synthetic methodology, total synthesis, natural-product semi-synthesis, process feasibility, and mechanistic chemistry.

  • Routes that survive scale and analog campaigns
  • Process-chemistry feasibility before commitment
  • Troubleshooting stalled synthetic sequences

Therapeutic areas

  • Oncology
  • Infectious disease
  • CNS / neurology
  • Metabolic disease
  • Cardiovascular disease
  • Psychiatric disorders
  • Autoimmune disorders

Modalities

  • Small molecules
  • Natural products
  • Targeted protein degraders
  • Peptides
  • Antibody-drug conjugates

Available for

Scientific advisory, fractional leadership, program review, AI evaluation, diligence, and pharmaceutical IP support.

Expert-network consultations are welcome when the question is chemical, not theatrical. I decline work I cannot stand behind.