Drug Discovery and Precision Medicine Using Empirical Mapping of Protein Variant Function

Technology Overview

A major reason that new medicines do not achieve their full potential is genetic variation among patients. Individual genetic variation drives variable drug response, primary and acquired drug resistance, unexpected toxicity and clinical trial failure. To overcome these obstacles when developing a new drug, researchers can now use direct, empirical preclinical measurement of how genetic variation alters protein function and its effect on a drug’s effectiveness, as well as examine the response of living cells to the drug.

Advantages of empirical mapping of variant function

Dr. Richard G. James

• Provides direct functional readout: measures protein activity and signaling in living human cells.
• Scales across thousands of variants: enables systematic mapping of genotype-phenotype relationships.
• Reveals drug sensitivity and resistance mechanisms: identifies functional escape mutations before clinical failure.
• Complements computational prediction: provides ground truth to benchmark and refine in silico models.

This much-needed novel approach to drug development has been generated by bioengineer Richard James, PhD, an expert in creating complex, multicomponent platforms for genome analysis. The platform developed by Dr. James and team empirically measures the effects of thousands of genetic variants on protein function in living human cells. The platform’s rapid, cloning-free technology enables identification of loss- and gain-of-function variants in homozygous or heterozygous states in living diploid cells. Platform applications include identifying drug-sensitizing or drug-resistant mutations, mapping allosteric and regulatory sites and prioritizing actionable drug targets in a pathway.

Platform components

• Saturation genome editing of endogenous human genes to assay all possible nucleotide and amino acid changes.
• Pooled variant libraries in living primary diploid cells to expedite analyses.
• Single-cell functional phenotyping (growth, signaling, secretion and gene expression profiles) to expand assayable functional effects.
• Microculture and secretion-linked readouts using hydrogel “nanovials” for functional studies with cell extrinsic readouts.
• Integrated variant-phenotype datasets suitable for clinical interpretation.

The James Lab has proof-of-concept data supporting use of the variant-analysis platform in multiple cell types. The research team functionally classified thousands of variants in clinically actionable genes (e.g., CARD11, TSC2). In these studies, the researchers identified gain-of-function and loss-of-function variants that explain patient phenotypes and drug responses via clinically relevant cellular behaviors. Preliminary data from this work include datasets suitable for clinical interpretation and drug targeting.

Conceptually, the James Lab’s variant-analysis platform complements artificial intelligence (AI) and machine learning computational models (e.g., AlphaFold) by providing empirical, in-cell measurements of protein activity and signaling. These datasets enable benchmarking and refinement of in silico predictors and provide functional ground truth for drug discovery programs.  

Applications of interest for partnership opportunities

1. Drug discovery
   • Identifying functional drug binding sites
   • Discovering resistance and escape mutations
   • Mapping allosteric regulation
2. Target validation
   • Determining which variants drive disease biology
   • Separating pathogenic from benign mutations
3. Precision medicine
   • Matching patients to therapies based on functional genotype
   • Predicting which patients will respond or not respond to the drug

 Who should partner with us?

• Leaders of drug discovery programs with drugs whose effectiveness is limited by unknown resistance or escape mutations.
• Industry researchers working with targets with high genetic heterogeneity or unclear functional variants.
• Leaders of precision medicine programs seeking functional validation of patient genotypes.
• Developers of artificial intelligence or machine learning programs seeking empirical datasets to train or benchmark predictive models.

Dr. James has experience with industry collaborations and leadership at start-up companies. He has extensive expertise in cell engineering, genome editing and disease modeling.

Stage of Development

• Preclinical validation: multiple genes and pathways in human cell lines and primary cells.
• Multiple functional readouts: growth, phenotype, phosphorylation, protein secretion.
• Scalable workflows: demonstrated throughput suitable for drug-target programs.

Partnering Opportunities

• Collaborative research opportunity
• Sponsored research agreement
• Consultation agreement
• Contracted collaboration
• Collaborative animal model development

Learn More

• Richard James, PhD, Seattle Children's Research Institute
• James Lab
• This variant discovery platform leverages similar technologies and complements other James Lab programs on immune control, engineered B-cell delivery (local and systemic) and humanized small animal model platforms for end-to-end, discovery-to-translation partnerships.

Publications

1. Biar CG, Wang ZR, Camp ND … James RG, et al. An integrated, scaled approach to resolve TSC2 variants of uncertain significance. Nat Commun. 2026;2026.01.16.699909.
2. Tejura M, Chen Y, McEwen AE … James RG, et al. A scalable approach to resolving variants of uncertain significance [Preprint]. bioRxiv. 2026:2026.2026.02.14.705848.
3. IGVF Consortium. Deciphering the impact of genomic variation on function. Nature. 2024;633(8028):47-57.
4. Meitlis I, Allenspach EJ, Bauman BM … James RG. Multiplexed functional assessment of genetic variants in CARD11. Am J Hum Genet. 2020;107(6):1029-1043.
5. Gelman H, Dines JN, Berg J … James RG, et al. Recommendations for the collection and use of multiplexed functional data for clinical variant interpretation. Genome Med. 2019;11(1):85.
6. Cheng RY, de Rutte J, Ito CEK … James RG. SEC-seq: association of molecular signatures with antibody secretion in thousands of single human plasma cells. Nat Commun. 2023;14(1):3567.

Last updated August 2026