Data Science-Driven
Drug Discovery
Related Sciences (RS) uses a proprietary AI/ML platform to identify the best new drug discovery opportunities for every disease, assembles decentralized global teams of top researchers to guide the science, and then invests in and leads the efficient discovery of valuable new medicines via preclinical-specialized R&D platforms
Building a Specialized New Investment Model
Innovating on biotech's operating, R&D, and business models itself can be a critical force-multiplier and accelerator in the quest to bring the next great generation of medicines to patients. As such, we study big questions like:
What Factors Increase the Chances of Success?
RS spent years quantitatively analyzing all of global biopharma's historical successes and failures in order to elucidate the specific factors that most impact a drug's odds of clinical success, and a company's chances of economic success. What if a new systematic set of principles and strategies based on these critical factors could significantly improve success rates? 1, 2, 5
What Innovations Enhance Risk-Reward?
Today ~99.7% of the world’s institutional investors have zero exposure to biotech, with only ~250 firms making 2+ therapeutics investments per year 3. What if new tech-enabled operating models and more efficient R&D strategies could improve the sector's accessibility and economic appeal, expanding capital availability for the drugs and companies that truly "deserve to be made"?
Are the Best Discoveries Made into Medicines?
Analysis of all current biomedical knowledge on the RS data platform reveals the surprising finding that ~75% of all target-disease opportunities with strong cumulative evidence of links have never been tried: 23,000+ opportunities spanning 3,800+ individual targets for 4,200+ diseases are just waiting to be made into promising new medicines. 4
Many Parallel Revolutions
The last decade's transformational innovations in drug discovery technologies, global contract R&D services, AI, biomedical data, therapeutic modalities, screening libraries, and remote connectivity collectively create an extraordinary new menu of advantages to discover valuable new medicines more efficiently and with greater odds of success than ever before.
Biomedical Data and AI
Approximately 250 million target-disease pairs collectively represent the "cures solution space" to treat and prevent all diseases. Selecting which target-disease pairs are worthy of investing significant research effort and capital is the hard part.
Fortunately, as human genetics evidence and other biomedical data sets continue to grow exponentially, strong new human evidence for hundreds of novel disease targets emerges each year, enabling data-driven approaches for prioritization.
And as Large Language Models and other forms of AI become increasingly capable, it becomes possible for the first time ever to systematically evaluate billions of interconnected research datapoints to help identify the very best new opportunities.
Virtual R&D Economy
Over the last decade, as large Pharma companies shuttered their early research centers (in favor of acquiring ~70% of their new drug pipelines from external biotech), a flood of talented R&D scientists made their way into global contract research organizations (CROs) dramatically expanding their offerings, capabilities, and scale.
As a result, a flourishing new virtual R&D economy now offers democratized, on-demand access to a wide range of highly specialized R&D capabilities, enabling biotech companies to 1) take better advantage of a broader swathe of new technologies to increase success rates, drug quality, pace, and efficiency; and 2) convert fixed overhead into fully variable expenses under lean, specialized management teams, eliminating the 40-60% of capex historically focused on building out labs and hiring generalists.
Remote Scientific Collaboration
Science is inherently global, and yet most US biotech remains local, with ~60-70% of US biotech VC invested in just 2 states.
Fortunately, the proliferation of remote collaboration tools unlocks extraordinary opportunities to reinvent traditional scientific staffing models to overcome geographic constraints and engage with the very best scientific talent wherever it may be found.
Large, fully virtual teams can now work together seamlessly across countries, research disciplines, vendors, and both academia and industry, collaboratively crafting world-class R&D strategies to improve quality and remove scientific blind spots.
Operating Model and Strategy
Biotechs have historically focused on shepherding a small number of programs from discovery through to advanced stages of clinical development. However, as top biopharma companies increasingly prioritize external acquisitions and early partnerships to fill 60%+ of their new drug pipelines, novel portfolio designs and business strategies emerge to enhance risk-adjusted returns.
Optimizing for earlier program exits can dramatically reduce exposure to the stages of the highest clinical failure risk. Designing larger, risk-diversified portfolios can mitigate binary outcomes while enhancing economies of scale and cross-program R&D synergies. And novel "asset-centric" corporate structures create the opportunity to tax efficiently sell individual programs without having to sell operations, unlocking new incentive structures and lean, evergreen value creation strategies.

A Fully-Integrated
Drug Discovery Ecosystem
RS combines 15+ modular innovations into a fully-integrated drug discovery platform designed to lower costs, maximize R&D technology advantages, and systematically mitigate key historical sources of risk.





RS Facets TM️ AI/ML Platform
Must 90%+ of drugs inevitably fail? Or can programs with far higher chances of success be identified prospectively? RS FacetsTM is a proprietary machine learning platform designed to ingest all activities in global biomedicine and systematically predict the best new drug discovery opportunities for every disease on an unbiased, quantified, fully explainable basis.
Innovation Stack
3 Proprietary Layers Unlock Extraordinary Insights




All of Biomedicine in One Dataset
RS curates, cleans, and integrates 70+ public, private, and RS-proprietary data sets covering virtually all activities in global biomedicine, from early basic research through to successful value creation, into a single giant time-resolved relational database--the RS Biomedical Atlas.

Quantitative Opportunity Ranking
RS then scores ~250 million possible drug discovery opportunities across 100s of proprietary metrics designed to systematically assess each program's relative risk-reward profile, recapitulating all of the considerations seasoned drug discovery investors use to evaluate a drug program.
Predictive AI/ML Models
Leveraging these two data layers, RS builds advanced machine learning models designed to predict key outcomes like the probability of clinical success or economic value creation, to globally rank millions of drug discovery opportunities and identify the very best ones for every disease.

Preclinical Specialization
On a risk-adjusted basis, preclinical drug discovery generates the highest risk-adjusted expected returns of any stage in drug development.2 RS specializes in this attractive stage of R&D, building specialized teams, methods, portfolio designs, and strategies to increase the odds of successful early program exits to the 600+ top biopharma acquirers.

Preclinical-Specialized Staff
Focusing purely on the goal of enabling world-class preclinical discovery at scale, RS is able to build hyper-specialized leadership teams, standing access to key technical advisors, and unique process management strategies that collectively optimize R&D quality, throughput, technology enablement, resource allocation, and end-to-end cost-efficiencies. By looking at successful drug discovery as an interdisciplinary, multi-modality, "assembly line", RS treats process design and vendor curation as an essential form of technology enablement to maximize the chances of discovering the most valuable drugs possible.

Data-Designed Preclinical Portfolios
RS creates and invests in a unique class of portfolio-based asset class to achieve a superior risk-reward profile with significantly better exposure to preclinical drug discovery as compared to a traditional small, clinic-focused biotech. Each RS "Constellation” represents an expansive portfolio of 15-25 of the highest-ranking drug discovery opportunities in a hot area of biological research with ascendant trends in commercial interest. By selecting only the best individual programs, and also structuring around portfolio-level risk diversification and R&D synergy objectives, RS creates a new way to invest efficiently, and at scale, in the stage of drug development that generates the very highest risk-adjusted returns.

Early Partnering and Exit Strategy
Preclinical drugs represent the majority of all asset acquisitions and the highest median risk-adjusted returns on capital invested. RS optimizes all aspects of its model—from initial program selection, to scientific team design, to its R&D package development, to pharma partnering and clinical strategies—to maximize prospective acquisition interest in completed preclinical drugs at attractive returns on capital. Each individual drug program is maintained in its own HoldCo enabling tax-efficient sale of individual drug programs without selling its operations.

Efficient New Operating Model
RS combines a novel decentralized team science model, portfolio-based R&D, a fully virtual operating model, and a tax-efficient and asset-centric corporate structure, to reduce its cost structures by 40%+, minimize required overhead and capital expenditures, and enhance their scientific quality, depth, breadth, and flexibility.

Decentralized Team Science
RS assembles field-leading academic scientists and clinicians from around the world into big, collaborative teams tailored to the unique expertise needs of each individual drug program, to work alongside RS and industry drug discovery specialists to craft best-of-breed R&D strategies. This “fractional CSO” model replaces the traditional combination of full-time generalists and passive quarterly “Scientific Advisory Board” members, with a more engaging team science model that yields both superior science and dramatically improved cost efficiencies.

Synergies and Economies of Scale
By designing RS constellations around a biology theme, clusters of drug programs which share biological similarities and pathways relationships can be advanced jointly and in parallel, generating significant cost and knowledge synergies through shared assays, advisors, and team time. Additionally, RS constellations are designed to generate high risk-adjusted returns inclusive of significant program attrition along the way, freeing RS to rigorously kill underperforming programs early in their development and redirect resources, without having to worry about binary outcomes.
Fully Virtual Architecture
RS drug programs operate leanly over a shared suite of RS capability platforms that provide access to the specialized interdisciplinary staff, labs, and technologies needed for world-class drug discovery without requiring any incremental overhead investments. By eliminating biotech restaffing requirements, capital-intensive lab build-outs, and geographic constraints, RS can build companies that leverage the best talent and capabilities wherever they may live while dramatically reducing fixed overhead and non-R&D uses of capital.

Decentralized R&D Platforms
RS continually curates and partners with the world's most advanced drug discovery service providers to provide centralized, preferred access to advanced R&D capabilities, broad therapeutic modalities, and specialized technical experts.

Curated Global R&D Partnerships
RS curates and builds long-term strategic partnerships with top research services organizations, discovery platforms, and technology companies around the world to maximize its chances of finding extraordinary new chemical matter, at preferred cost structures, and with uniquely aligned incentives aligned for quality and success. RS currently works with 8 major R&D partners, including drug discovery leader, Evotec, which provides RS with access to its global network of cutting-edge laboratories, multi-modality screening capabilities, and 1,000’s of expert drug discovery scientists.
Discovery Technologies
Drug discovery technologies continually advance as new high throughput screening and robotics systems, compound libraries, in vitro and in vivo models, reagents, assays, and analysis methods, and in silico/AI drug design tools all improve and compound on each others' benefits. RS continually curates and centralizes access to the latest discovery technologies to maximize its companies' end-to-end discovery efficiency, pace, quality, and overall odds of success.
Therapeutic Technologies
Different modalities offer unique advantages for different types of targets. To take maximal advantage of these important new capabilities in a modality-agnostic manner, RS curates and partners with specialist vendors, builds teams of technical advisors, and often pursues parallel approaches for each target. At current, RS can make 10+ different types of medicine.

Indication Strategy
Leveraging its Facets™ data platform, clinical landscape mapping, and working with integrated teams of top clinician-scientists, hospitals, and academic research groups, RS systematically identifies the best disease opportunities for each program, crafting “pipelines-in-a-product” that maximize predicted expected odds of clinical success, patient impact, and economic value creation.
Team
RS is led by a multi-disciplinary team of drug discovery, data science, and venture capital veterans who have founded, built, and led biotech companies worth billions, and is backed by a luminary group of investors.
























Pipeline
RS builds, launches, and manages one new company portfolio every 1-2 years, each of which is comprised of a “constellation” of the top 0.001% of all drug opportunities in an ascendant area of research and commercial interest.
Vision
Improving drug discovery efficiency and success rates to benefit all of biomedicine's important stakeholders:
Patients
A greater number of transformational new medicines for virtually all types of disease are discovered sooner and successfully brought to market more often.
Researchers
Breakthrough research is successfully translated into medicines more often, and our new model enables leading researchers to contribute to biotech R&D without needing to leave academia.
Entrepreneurs
Biotech company failure is significantly reduced, driving significantly lower job turnover and training a deeper bench of capable biotech operators for the next generation of drugs.
Pharma
Supply of high quality, clinic-ready drugs is dramatically increased and made available at acquisition prices that both incentivize biotech and are sustainable for pharma’s own economic models.
Investors
Better biotech risk-reward drives a much greater proportion of investor wins broadening interest among institutional investors to fund future biotech innovations.