Medication response intelligence

Make medication response predictable.

Phenomics Health is building the intelligence platform for safer, smarter medication decisions — integrating pharmacogenomics, pharmacometabolomics, clinical context, medication exposure, outcomes, and AI into a response-first decision architecture.

68 PGx genes in PredictScript™
200+ Rx and OTC medications measured
44 publications supporting the foundation
Medication Response Intelligence

AI Identifies the Response Phenotype

Medication response cannot be predicted by genetics, metabolomics, lab testing, or AI alone.
It emerges when these signals are integrated into a response phenotype.

Patient Signals
Genetics
Medication Exposure
Lab Results
Clinical History
Drug Interactions
Environment & Lifestyle
Prior Outcomes
AI Identifies the Response Phenotype
Medication Response Phenotype
Decision Intelligence
Right Therapy
Better Dose
Lower Toxicity
Better Timing
Better Outcomes
The opportunity

Medication response is too often discovered after failure.

The hidden drivers of response — genetics, medication exposure, interactions, adherence, clinical history, labs, environment, and prior outcomes — are usually fragmented across systems.

40%medications are ineffective
50%medications are not taken
55%medication dose is ineffective
33%unknown medications
53%drug interactions from unknown medications

Phenomics makes these signals measurable and modelable. The platform is designed to create response intelligence before medication selection, not just reaction after ineffective therapy.

See the approach
Platform

From prescribing workflow to medication intelligence.

PhenomicsAI connects diagnostics, patient data, and AI-inferred phenotypes into a practical decision layer that can be embedded where medication choices are made.

01

Integrate patient signals

Combine PGx, PMx, direct medication exposure, clinical history, labs, outcomes, EHR and claims context, and curated evidence.

02

Infer response phenotypes

Use PhenomicsAI and clinically auditable data pipelines to identify patient-specific patterns that influence medication response, risk, timing, and dose.

03

Guide better decisions

Deliver intelligence for treatment optimization, risk stratification, population analytics, and life-sciences evidence generation.

Predict

Response + risk

Identify patients at risk of failure, toxicity, interaction, or avoidable utilization.

Select

Therapy + dose

Support medication and dose choices based on patient-specific response signals.

Monitor

Exposure + outcomes

Measure what patients are taking and connect exposure to clinical response.

Optimize

Adjust + improve

Recommend next-best actions, alternatives, adherence interventions, or monitoring.

Precision ecosystem

One company. Multiple medication intelligence layers.

Phenomics Health combines clinical laboratory capabilities with PhenomicsAI to connect predictive intelligence, direct measurement, and enterprise medication-response workflows.

PredictViewPGx™

Expanded next-generation pharmacogenomics. 170+ medications and 68+ genes, with broader actionable coverage than legacy panels.

SyncView™Rx

Direct medication exposure intelligence for prescription and OTC medications, supporting adherence insight, medication reconciliation, and safety workflows.

New

PrecisView™ Peptide

Mass-spec measurement of circulating peptide exposure for tirzepatide, retatrutide, CJC-1295, Ipamorelin, BPC-157, TB-500, and related compounds.

PhenomicsAI

Multi-agent clinical AI platform. Fast Path for routine cases plus Smart Path escalation for complex polypharmacy, rare variants, and conflicting signals — with provenance and audit trail.

For Health Systems

Enterprise medication intelligence for high-risk cohorts, medication reconciliation, avoidable adverse events, readmission reduction, and value-based care performance.

For Payors

Test-independent analytics on existing EHR and claims data to quantify spend leakage, polypharmacy risk, hidden DDI burden, and opportunities for MLR and UM optimization.

Who we serve

One platform.
Multiple high-value workflows.

Medication-response intelligence can support the people making treatment decisions, the organizations managing risk, and the partners building evidence at scale.

Clinicians & Health Systems

Clinical decision support
  • Reduce failed first-line therapy and cycling
  • Identify hidden DDIs and medication reconciliation gaps
  • Improve STARS ratings and value-based performance
  • Lower avoidable ED visits and readmissions

Payors & Risk Programs

Risk stratification & value
  • Identify high-risk polypharmacy members before costs escalate
  • $74–$126 net PMPM savings in targeted cohorts
  • Reduce pharmacy waste and avoidable hospitalizations
  • Shared savings and PMPM contract models

Life Sciences & Biopharma

Data, models & RWE
  • Identify likely responders for trial enrichment
  • Generate high-quality real-world evidence faster
  • Optimize post-marketing surveillance
  • Data and AI partnership models available

Population Health & Learning Systems

Continuous improvement
  • Build learning health systems around medication outcomes
  • Feed outcomes back into better models
  • Support value-based care and ACO performance
  • Population-level utilization intelligence
Company

Company

Learn about the leadership, founders, laboratory foundation, and company operating model behind Phenomics Health.

Collaborative foundation

Built across academic, clinical, and translational networks.

View Evidence

Phenomics Health’s foundation spans academic validation, clinical research, informatics, medication exposure, and industry translation.

University of Michigan
Rutgers
Vanderbilt
Wayne State University
Duke
Cleveland Clinic
Myriad Genetics
University of Michigan
Rutgers
Vanderbilt
Wayne State University
Duke
Cleveland Clinic
Myriad Genetics
Partner with Phenomics

Launch a medication-response intelligence program.

Talk with Phenomics Health about programs for clinical decision support, medication-risk stratification, peptide monitoring, health-system cohorts, lab channels, and life-sciences partnerships.