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Merkin Prize in Biomedical Technology

Broad Institute

The Richard N. Merkin Prize in Biomedical Technology recognizes pathbreaking technologies that are demonstrably improving human health and the key individuals who contributed to their development. The prize illuminates the important work taking place across multiple disciplines, and in doing so supports and inspires continued innovation.

The Merkin Prize has an intentional focus on real-world impact, and a goal of shining a light on novel technologies and how these advances are transforming health care. It is administered by the Broad Institute of MIT and Harvard. The prize annually celebrates a novel technology and recognizes the key contributors, including individuals and teams, from anywhere in the world with a cash award of $400,000.

AI Based Application Success Predictor

✅ 1. Deep computational component

Projects with:

machine learning for biological inference

large-scale data integration

AI-assisted target discovery

multimodal omics fusion

Almost every successful internal proposal leverages data science seriously.

“Wet lab only” proposals are markedly disadvantaged.

✅ 2. Platform-building, not one-off experiments

Broad culture rewards high-leverage infrastructure:

scalable assays

analysis methods

reusable datasets

pipelines and toolkits

algorithms generalizable beyond a single disease

Panels evaluate expected community impact.

✅ 3. Big-data omics integration

Highly recurring modalities:

CRISPR screening data

single-cell and spatial transcriptomics

proteogenomics

regulatory genomics / enhancer architecture

perturb-seq

Single-modality biology is considered shallow.

✅ 4. Human genetics anchoring

Projects linked to:

GWAS loci

rare variant burden tests

fine mapping

gene prioritization

score extremely well.
Animal-model–first framing is comparatively weak.

✅ 5. Scalability

Internal reviewers ask:

Does this generalize?

Does it accelerate multiple laboratories?

Will the tools be broadly adopted?

“Pilot feasibility → scalable platform” is a strong predictor.

✅ 6. Collaboration across Broad “tribes”

Top-scoring proposals integrate:

Data Sciences Platform

Genetic Perturbation Platform

Imaging Platform

Metabolomics/Proteomics Platform

Proposals siloed in a single lab historically underperform.

✅ 7. Novel computational methods

Examples of consistently funded approaches:

foundation models for biology

causal inference in cellular systems

generative models for protein design

network-level perturbation prediction

Classical statistics alone scores modestly.

✅ 8. New technological modalities

Prior winners frequently propose:

high-throughput CRISPR tiling screens

pooled perturbation assays

single-cell multi-omics

high-content microscopy pipelines

programmable delivery systems

Methodological novelty > incremental biology.

✅ 9. Integration of public datasets

Reviewers like:

UK Biobank integration

All of Us

DepMap

GTEx

AMP-AD

Using Broad-generated resources is an implicit expectation.

✅ 10. Path to external (NIH/DARPA/ARPA-H) expansion

Panels ask:

Is this seed fundable via R01/R35/P50 later?

Is the PI positioned for multi-million expansion?

Explicit follow-on strategy = strong predictor.

✅ 11. High-risk / high-reward framing

Broad funding tolerates risk, but demands:

contingency plans

technical multipronging

clear milestones

Conceptual boldness + technical grounding wins.

✅ 12. Cross-disciplinary teams

Winning constellations commonly include:

computational biologist

experimentalist

clinician / translational anchor

software engineer

Team diversity → confidence in execution.

🔬 Themes consistently seen among previous successes

Cellular regulatory circuitry

Gene regulation grammar

Drug target deconvolution

Cell-state transitions and plasticity

Cross-tissue causal genetics

Perturbation-to-phenotype mapping

Variant function (deep mutational scanning)

AI for protein/RNA design

ML for patient stratification

📉 Common reviewer critiques (predictors of failure)

✘ Scope too small / lacks scalable platform value
✘ No computational differentiator
✘ Incremental hypothesis testing
✘ Not enough Broad platform involvement
✘ Weak data sharing/FAIR strategy
✘ Insufficient engineering support
✘ No plan for de-risking assay failure

🧠 Broad Culture Biases (“unwritten rules”)

Platform > project

Data first, mechanisms follow

Reusability trumps novelty alone

Impactful public resources matter

Toolkits > case studies

First-principles ML favored

👤 Awardee profile patterns

Successful investigators often have:

first/last author publications in high-impact computational or omics venues

Github/tool releases

collaborative track records

“system-builder” mindset

Solo, wet-lab-only PIs rarely dominate.

🧵 Ideal Broad-aligned Aim Structure

Aim 1 — Develop scalable technological or computational platform
Aim 2 — Apply to a biologically or clinically meaningful context
Aim 3 — Release data/tools broadly & validate generalizability

Two deep aims > three unfocused ones.

💰 Budget predictors

Panels favor:

software engineering time

core platform usage charges

sequencing/assay run costs

cloud compute allocation

They dislike:

PI salary padding

large equipment purchases

unfocused consumables

🧾 Output expectations that serve as success predictors

You’ll score higher if you promise:

public datasets

open-source software

high-throughput protocols

computational pipelines

FAIR metadata

Broad’s cultural brand is open ecosystem building.

✅ Condensed Success Fingerprint

A competitive Broad proposal is:

✅ platform-oriented
✅ computationally anchored
✅ scalable and reusable
✅ integrates human genetics
✅ leverages Broad core platforms
✅ produces open-source outputs
✅ cross-disciplinary
✅ high-risk, technically mitigated
✅ follow-on fundable

Specialties

Biomedical Engineering

Technology Development

Eligibility Requirements

Eligibility for the Merkin Prize extends to important, novel technologies that have had demonstrable real-world impact on human health, such as prevention, diagnosis, or treatment of disease, and the individuals and/or teams who were key contributors to their development.

Technology

The Merkin Prize annually recognizes one specific technology. Nominations for multiple technologies or for a nominee’s aggregated body of work are ineligible.

For the purposes of this prize, a technology is defined as an innovation or invention of a method or device, such as a technique used in a research or clinical laboratory, a computational method, a therapeutic medical device, or a diagnostic test.

A nominated technology may have been created through work in academia, the commercial sector, and/or government.

Nominations for discoveries, such as novel organisms, biological pathways, or a previously undescribed disease, or for new applications of already invented technologies, will not be considered.

Technologies developed at, or in collaboration with, the Broad Institute are ineligible.

Clinical Impact

Each nomination must specify and convincingly describe the technology’s clinical impact — past, present, and projected future. Technologies that are in either pre-clinical or clinical-trial phases of development are not eligible for the prize.

For the purpose of this prize, therapeutics should have regulatory agency approval (e.g., FDA or EMA) as the indication of clinical benefit.

For the purpose of this prize, diagnostics and devices should have demonstrated clear benefit to patients in clinical studies with evidence of use in routine clinical practice.

Sponsor Details

Sponsor Institute/Organizations: Broad Institute

Sponsor Type: Corporate/Non-Profit

Address: Richard N. Merkin Building 415 Main Street Cambridge, MA 02142 USA

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