Population-Specific
Analysis
Predict how your compound behaves across genetically diverse populations before clinical trials.
THE CHALLENGE
Genetic diversity affects drug response. Clinical trials fail when compounds behave unpredictably across populations. The FDA and EMA now require evidence of pharmacogenomic variability in regulatory submissions ---- and 40% of drugs show clinically significant differences
WHAT WE DELIVER
Our analysis framework integrates structural bioinformatics, biophysical simulations, and clinical genetics to predict how genetic variants reshape protein structure, dynamics, and drug-target interactions across human populations. Our approach builts on a decade of peer-reviewed research from Prof. Alejandro Giorgetti's laboratory at the University of Verona.
OUR METHODOLOGY
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Variant Mapping
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Population-associated variants from GnomAD, ClinVar, and PharmGKB mapped onto protein structures
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Structural Dynamics
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Molecular dynamics simulations reveal how variants alter protein folding, dimerization, stability, and active-site geometry
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Functional impact
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Assessment of efficiency, receptor signaling, and regulatory behavior changes caused by each variant
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Drug-Target interaction
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Prediction of altered binding affinities, and downstream efficacy across variant-bearing protein isoforms
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YOUR DELIVERABLE
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Population Risk Report
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Variant-by-variant risk matrix for each target population, with accurate reporting on confidence.
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Variant Impact Matrix
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Structural and functional consequences of every relevant mutations are mapped to your compound's binding site.
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Drug-Target Interaction Analysis
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Predicted binding affinity changes, residence time shifts, and efficacy modulation per population group
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Clinical Strategy Recommendations
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Population-specific considerations, inclusion/exclusion criteria guidance.
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Report Support Package
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Full technical report with data, methodology, actionable recommendations, and debrief calls to discuss findings.
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SCIENTIFIC FOUNDATION
Our framework is built on a body of peer-reviewed research demonstrating how genetic variants alter protein dynamics, stability, assembly, and drug interaction --- spanning rare pathogenic mutations, common population variants, and protective alleles
Protein Dynamics & Catalysis
AADC enzyme flexibility and asymmetry mechanisms linking structure to genotype–phenotype relationships (Bisello et al., Protein
Science 2023)
Receptor Pharmacogenomics
Oxytocin receptor A218T variant shown to alter receptor stability and signaling, modulating drug response (Meyer et al., Mol. Psychiatry 2022)
Protective Alleles for Drug Discovery
APOB truncating variant reducing LDL/CAD risk-informing therapeutic targeting by mimicking natural protection (Atherosclerosis
Plus 2022)
Additional validated applications: PH1/AGXT dimerization variants (Dindo et al., Biochimie 2016), BCKDK gain-of-function in metabolism (Maguolo et al., Genes 2022),
GPCR modeling tools — pyGOMoDo (Ribeiro & Giorgetti, Bioinformatics 2023), and ongoing AADC genotype–phenotype correlation studies (Bisello et al., FEBS Open Bio 2025).
De-risk your pipeline with population-level insight.
Book a 15-min review Info@discoverapharma.com