Digital Endpoint & AI R&D Pipeline | Supporting Drug Development

Evidence infrastructure that helps drugs win trials.

Delve Health invests in and develops digital endpoints and AI layers that improve endpoint sensitivity, reduce operational risk, and extend evidence generation across the drug lifecycle—from Phase II/III execution to post-market follow-up and real-world evidence.

How we define “pipeline”

We do not develop drugs. We develop the digital endpoints, AI intelligence, and operational systems that de-risk clinical development and strengthen evidence packages—especially in programs where remote measures, adherence, and real-world signals matter.

Lower operational risk Stronger endpoint sensitivity Faster decision cycles Audit-ready evidence

What makes this investable

Digital endpoints only create value when operationalized end-to-end. Our R&D focuses on signal integrity, compliance, auditability, and correlation to clinically meaningful outcomes—then scales those workflows across programs.

Missingness & QC Retention & adherence Gold-standard correlation AI insight layer

R&D pipeline: Digital endpoints → AI → lifecycle evidence

A staged view of our R&D efforts—from endpoint thesis formation through AI intelligence and post-market evidence workflows—built to support drug programs across therapeutic areas.

1
Thesis validated

Endpoint thesis & feasibility

Identify where digital measures can materially strengthen endpoints and trial execution.

  • Cardiovascular: HRV, arrhythmia burden, activity tolerance
  • Oncology: fatigue, functional decline, cardiotoxicity signals
  • Metabolic/obesity: activity, sleep, adherence patterns
  • Respiratory: symptom-linked physiology, home monitoring
2
Active development

Digital endpoint development

Translate hypotheses into measurable, auditable endpoints for Phase II/III designs.

  • Wearable-derived digital biomarkers
  • Sensor-triggered ePRO / symptom capture
  • Composite endpoints (sensor + PRO + clinical)
  • Correlation vs. gold standards (ECG, echo, labs)
3
Deployed & expanding

AI & evidence intelligence

Turn raw trial data into decision-grade insight for development and clinical operations.

  • Compliance and adherence prediction
  • Signal quality, missingness, and QC automation
  • Early safety / tolerability pattern flags
  • Protocol risk & feasibility modeling
4
Scaling programs

Post-market & lifecycle evidence

Extend evidence generation beyond approval and strengthen long-term monitoring and RWE.

  • Post-market clinical follow-up (PMCF)
  • Real-world evidence (RWE) workflows
  • Long-term safety and effectiveness monitoring
  • Digital companion strategies for adoption

JPM Bio positioning statement

Delve Health invests in and develops digital endpoints and AI infrastructure that de-risk clinical development, accelerate evidence generation, and improve post-approval adoption across multiple drug classes.

We advance initiatives only when we can operationalize the full chain of evidence—signal integrity, compliance, auditability, and correlation to clinically meaningful outcomes.

Drug classes and programs supported

Our R&D priorities align to areas where digital endpoints can increase endpoint sensitivity, reduce missing data, and strengthen evidence packages for development teams and medical affairs.

Cardiovascular

Arrhythmia burden, functional tolerance, physiologic trends, patient adherence.

Oncology

Fatigue and functional decline, cardiotoxicity signals, symptom-linked monitoring.

Metabolic / Obesity

Sleep, activity patterns, behavior-linked adherence, sustained engagement at scale.

Respiratory

Home monitoring, symptom-linked measures, engagement support for chronic programs.

Attending JPM Bio events

If you are reviewing companies for JPM Bio access, we can share a concise overview of our R&D pipeline, current programs, and how our digital endpoints and AI layers support drug development and lifecycle evidence.