The combination Design Engine for solid tumors.

We predict the target combinations that shut down escape routes in solid tumors, where 90% of cancer deaths occur.

Problem

Combination therapy is standard. Choosing the right targets is still guesswork.

The number of viable multi-target combinations far exceeds what any preclinical screen or clinical trial program can test one at a time.

Preclinical synergy does not translate cleanly

Cell-line synergy metrics, HTS screens, and simplified model systems often miss the clinical context that determines patient benefit: resistance history, toxicity, line of therapy, biomarker context, and tumor evolution.

Solid tumors escape single-agent pressure

Most solid tumors adapt through redundant pathways, lineage plasticity, immune evasion, and resistance rewiring. Pharma needs a systematic way to identify combinations before committing to expensive trials.

90%of cancer deaths occur in solid tumors

30-70%relapse rates in major NSCLC settings

$B+wasted on poorly translated combinations

Solution

Clinical outcome training Resistance-aware prioritization Cross-modality NSCLC

Ingest

Clinical trial and real-world outcomes, integrated with mechanistic and biological evidence.

Rank

Score combinations of 2+ targets by predicted clinical benefit, and surface the patient subgroups most likely to respond.

Confirm

Outputs are confirmatory studies before a program advances.

Validation

Benchmarked against real clinical outcomes.

0.89AUC, how reliably EMphora ranks combinations in clinical cohorts

0.80AUC, how reliably EMphora ranks combinations using real-world patient records

0.87Precision@5, the share of EMphora's top 5 predicted combinations confirmed as true responders

0.88AUC, EMphora's performance in Temporal Cross Validation

Team & Advisors

Computational drug discovery, oncology translation, and company-building experience.

Mi Yang

Founder & CEO

Mi earned his PhD at Heidelberg University under Prof. Julio Saez-Rodriguez in cancer systems biology, publishing in Nature Biotechnology and Cell Systems. He led the NCI-CPTAC DREAM Proteogenomics Challenge, coordinating 100+ scientists globally, then joined Stanford under Prof. Ash Alizadeh to build a computational reverse translation platform.

Bharath Kumandan

Advisor, Business Operations

15+ years scaling biotech from pre-seed through IPO. Founding team member at Aligos Therapeutics, built all non-scientific functions, and led drafting of the S-1 business section ahead of the $150M IPO. Previously VP of Operations at Gordian Biotechnology. Earlier career in life sciences investment banking and strategy consulting.