The problem
Biotech investing is structurally inefficient. Over 44% of microcap biotech stocks have fewer than two analysts covering them. More than 17% have zero coverage. The stocks that need the most analysis get the least.
Valuations hinge on binary outcomes. A Phase 3 readout can double a stock or cut it in half overnight. Most investors lack the tools to evaluate the underlying science, so they're left parsing press releases and guessing.
The information that matters most — whether a drug's biological rationale is sound — is buried in genomic databases and academic papers that most market participants never read.
The genetic edge
Three landmark studies have quantified something drug developers have suspected for decades: drugs that target genes with genetic links to the indicated disease are significantly more likely to succeed in clinical trials.
The support of human genetic evidence for approved drug indications.
Nature Genetics, 2015.
Analyzed all approved drugs and found genetically supported targets were 2x more likely to reach approval. The proportion of genetically supported mechanisms rises from 2% at preclinical to 8.2% among approved drugs.
Are drug targets with genetic support twice as likely to be approved?
PLOS Genetics, 2019.
Replicated and refined Nelson's finding with updated data. Confirmed the 2x effect, especially when causal genes are clear — Mendelian traits and coding variants from GWAS.
Refining the impact of genetic evidence on clinical success.
Nature, 2024.
The most rigorous analysis to date. Estimated 2.6x greater probability of success for genetically supported targets. The effect holds across therapy areas and development phases, and improves with increasing confidence in the causal gene.
The takeaway is straightforward. If a drug targets a gene that human genetics says is involved in the disease, that drug is roughly 2–3x more likely to make it through clinical trials. In a sector where over 90% of drugs fail, this is one of the strongest predictive signals available.
What BioTickers does
BioTickers applies this research systematically across 700+ public biotech and pharma companies. For every drug in clinical development, we ask one question: does the target gene have genetic evidence linking it to the indicated disease?
We score each drug-target-disease combination using germline genetic data from the Open Targets Platform, drawing on genome-wide association studies, rare variant burden tests, ClinVar pathogenic variants, Genomics England panels, and other curated genetic databases. The result is a genetic support score from 0 to 1 for every pipeline asset.
Companies whose lead clinical assets have strong genetic support (score ≥ 0.80) enter the GS Basket — an equal-weight portfolio we track against the XBI biotech index and S&P 500. This is not a trading strategy. It is a lens for understanding which pipelines are built on firmer biological ground.
What this is not
BioTickers is an educational and informational tool. It is not financial advice.
Genetic support is one signal among many. It says nothing about a company's cash runway, management quality, competitive positioning, manufacturing capability, or commercial strategy. A high genetic score does not mean a drug will succeed. A low score does not mean it will fail.
What it does mean: the underlying biology is on firmer ground. In a sector defined by binary outcomes and information asymmetry, that is worth knowing.
Data sources
- Genetic evidence: Open Targets Platform (EMBL-EBI & Wellcome Sanger Institute)
- Clinical trials: ClinicalTrials.gov (U.S. National Library of Medicine)
- Drug-target mappings: ChEMBL (EMBL-EBI)
- Stock data: Yahoo Finance