Every weight, threshold, and hard-stop flag in the Bridge BioHealth Go/No-Go Decision Engine is grounded in peer-reviewed drug attrition research, FDA guidance documents, and published industry benchmarks.
~10%
Overall clinical success rate from Phase I to approval
Hay et al., Nature Biotechnology 2014
$2.6B
Average capitalized cost to bring one drug to market
DiMasi et al., Journal of Health Economics 2016
56%
Of Phase II/III failures due to lack of clinical efficacy
Waring et al., Nature Reviews Drug Discovery 2015
Drug development is the most capital-intensive, high-attrition endeavor in science. With only ~10% of programs that enter Phase I ultimately reaching approval, and the average cost exceeding $2.6 billion, the cost of a wrong Go decision is catastrophic. Conversely, a wrong No-Go decision kills potentially life-saving therapies.
The Bridge BioHealth Decision Engine was designed to address a specific gap: most early-stage Go/No-Go decisions are made informally, by teams with inherent confirmation bias toward their own programs. Our tool provides a structured, anonymized, externally-calibrated framework that forces systematic evaluation across all five evidence domains — before sunk costs accumulate.
Critically, the tool is designed to work for any lead source — wet lab, computational, AI-generated, or theoretical — because the evidence framework evaluates the quality of the data, not the method by which the compound was identified.
Each domain is scored independently on a 0–100% scale, then combined using evidence-based weights derived from published drug attrition data.
Efficacy failures are the #1 cause of clinical attrition (56%, Waring et al. 2015). MoA validation, in vitro/in vivo efficacy, selectivity, reproducibility, and independent replication are the strongest early predictors of clinical success.
Evaluated Sub-Factors:
Certain findings trigger an automatic NO-GO verdict regardless of overall score. These reflect real regulatory and scientific showstoppers that cannot be overridden by strong performance in other domains.
Automatic NO-GO regardless of overall score. Genotoxic compounds cannot advance to human trials without resolution.
Automatic NO-GO. Cardiac safety is a primary regulatory concern. hERG IC50 < 30× therapeutic concentration requires medicinal chemistry resolution.
Automatic NO-GO. Single-lab, irreproducible data is the most common cause of late-stage failure and cannot support IND filing.
Score thresholds are calibrated against published industry attrition data to ensure verdicts reflect real-world program quality distributions.
Score: 72–100
Top quartile of early-stage programs. Evidence base supports advancement. ~15–25% probability of reaching Phase II (vs. ~5% industry average from discovery).
Score: 52–71
Second quartile. Meaningful promise with material gaps. Conditional advancement supported, contingent on resolving identified concerns. ~70–80% attrition at this stage.
Score: 35–51
Below median. Multiple significant deficiencies. Focused de-risking or pivot strategy recommended before committing further resources.
Score: 0–34 or Hard-Stop
Insufficient evidence base or critical safety/integrity flag. Program deprioritization, pivot, or archiving recommended.
The scoring framework is grounded in the following peer-reviewed publications and regulatory guidance documents. Click any citation to see how it informs the scoring methodology.
Self-Reported Data
The tool relies on user-submitted assessments. Scores reflect the quality and honesty of the input data. Overconfident or incomplete submissions will produce inaccurate results.
Modality Generalization
The current framework is optimized for small molecule programs. Biologics, gene therapy, and cell therapy programs may require modality-specific weighting adjustments.
No Therapeutic Area Specificity
Domain weights are averaged across therapeutic areas. Oncology, CNS, and rare disease programs have different attrition profiles that are not fully captured in the current version.
Not a Substitute for Expert Review
This tool is a structured decision-support framework, not a replacement for expert scientific judgment. Peer review and expert consultation are strongly recommended for high-stakes decisions.
The scoring framework is reviewed and updated quarterly by the Bridge BioHealth scientific team. Updates incorporate new published attrition data, regulatory guidance changes, and feedback from expert peer reviewers.
Annual subscribers receive automatic access to methodology updates and are notified of any changes that may affect the interpretation of previously generated reports.
We welcome suggestions from the scientific community for additional literature that should inform our scoring methodology.
Contact our scientific teamApply this evidence-based framework to your own compound or program. Anonymized, confidential, and grounded in the same published data cited above.