We Build a New
Class of Biotech

Related Sciences (RS) is a data-driven drug discovery studio. RS uses a proprietary machine learning platform to identify the best new drug discovery opportunities for every disease, organizes them into structured investment portfolios, and then operates them leanly over a specialized platform designed to take full advantage of the last decade's transformational R&D and productivity innovations.

Extraordinary Science Deserves a Fresh Model

Scientific entrepreneurs build biotech companies to create better medicines. But what if building a better biotech company could enable those entrepreneurs to succeed more often? We view innovating on biotech's operating, R&D, and business model itself as a critical force-multiplier and accelerator in the quest to bring the next great generation of medicines to patients as quickly as possible. As such, we focus on 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 this could significantly improve success rates? 1, 2, 5

What Models Might 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 operating and financial models could improve the sector's accessibility and economic appeal, dramatically expanding capital availability for the drugs and companies that truly "deserve to be made"?

Are the Best Discoveries Being 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

Revolutionary Biotech Design

The last decade's parallel revolutions in biomedical data, R&D technologies and services, new therapeutic modalities, AI, and remote connectivity, collectively create an important new menu of possibilities to re-envision how biotechs are designed and operated to significantly improve their capital efficiency, scientific quality, and overall odds of success.

Opportunity Selection

Approximately 250 million target-disease pairs collectively represent the current solution space to treat, prevent, and cure all diseases. Choosing among them into which to invest significant research effort and capital is the hard part.

Fortunately, as biomedical data sets continue to grow exponentially, it becomes increasingly possible to quantitatively evaluate key built-in characteristics that shape each opportunity's risk-reward profile.  As examples, it has been shown that drug programs with strong human genetics evidence of links to a disease have ~3x+ higher rates of clinical success than those that do not, and, structurally enabled targets with validated assays have a greater chance of efficient, successful drug discovery than those without.  

Prioritizing those opportunities with the very best risk-reward characteristics can significantly increase a company's built-in  odds of both clinical and economic success.

Portfolio Design

At every step in the R&D funnel, a program's unique attributes matched to the historical success rates of programs with similar attributes, roughly inform its odds of advancing or failing.

Utilizing these inputs, portfolio theory offers a range of valuable levers that can help to mitigate or offset these risks through design and scale. For example, by prospectively building expected attrition into portfolio size, some set number of programs are likely to advance, enabling the winners to pay for the losers on a risk-adjusted basis. Scale diversifies away the risk of the  binary outcomes often seen with a single "lead program".

Further, economies of scale apply materially to drug R&D.  At scale, both vendor pricing and partnering opportunities often improve, and working on multiple biologically related programs can unlock cost, time, and knowledge synergies such as common assay development or shared scientific advisors.

Optimizing portfolio scale, design, and structure offers important new ways to improve biotech efficiency and risk profiles.

Operating Efficiency

A wide range of new opportunities exist to capture greater efficiencies in the way biotechs are staffed and operate.

First, despite individual biotechs focusing on unique research opportunities, a significant portion of capital -- we estimate as high as 60% of funds raised -- is allocated to rebuilding nearly identical scientific, business, laboratory, advisory, and back office capabilities, over and over again. If companies were designed instead to share investment in, and variabilize use of, both generalist and specialized capabilities needed on an infrequent basis, capital expenditures, staffing time, and operating costs could all be materially reduced, while expanding shared investment into the  quality of the capabilities themselves.

Additionally, new virtual team structures and remote collaboration models unlock extraordinary new opportunities to overcome geographic constraints and engage with the very best scientific talent wherever it may be found. Large virtual teams can work together to craft world-class R&D independent of typical "biotech hubs", and fractional advisors and consultants can both deepen and broaden the team's collective expertise, removing blind spots.

R&D Advantages

Over the last decade, as pharma companies shuttered major R&D centers, a flood of talented scientists made their way into contract research organizations, broadening their capabilities. Today this "virtual R&D economy" is flourishing, having matured into a wide range of large scale, fully-integrated, multi-modality, high quality R&D providers and a large ecosystem of smaller technology enabled specialist firms, on offer to biotech companies everywhere.

Against the backdrop of continuous rapid technology innovation, this sector helps to democratize access to the kinds of R&D capabilities that used to be reserved only for Pharma. New drug discovery methods, compound libraries, research tools, AI and analytical capabilities, and a wide range of novel therapeutic modalities, are now available on an on-demand basis.

By treating access to and curation of this global contract research ecosystem as a strategic asset, biotechs can now integrate a much wider range of technology advantages across virtually all aspects of the research, discovery, and development cycle. By architecting firm capabilities around hybrid internal-external, or fully externalized R&D models, biotechs can improve the quality of their science, alongside their cost structures, timelines, and overall breadth of possibilities.

Unique Advantages
Built Into Every RS Company

RS combines 15+ modular innovations across 4 key areas into a singular shared platform that powers each new company RS builds, lowering their R&D costs, providing curated access to a wide range of enabling technologies, specialists, and partners, and minimizing capital investment in overhead.

A New Data Science Platform to Find the Very Best Opportunities

A Specialized New Model for Preclinical Drug Discovery

A New Company Architecture Designed to Optimize Efficiency

New Centralized Platforms to Maximize R&D Advantages

Using Data Science to Identify

The Best Opportunities

Every new medicine has a range of important built-in characteristics that ultimately shape its risk-reward profile.  How strong and well-validated is the evidence?  How hard will it be to make?  Is the commercial timing right?  RS FacetsTM is a first-of-its-kind data science platform designed to ingest all activities in global biomedicine and systematically predict the best new drug discovery opportunities on an unbiased, quantified, explainable basis.

RS Facets™️

Prioritization Engine

See Everything

All of Biomedicine in One Dataset

Assess Risk

Quantitative Opportunity Ranking

Choose Wisely

Predictive Machine Learning

A Specialized New Model for Investing in

Preclinical Discovery

On a risk-adjusted basis, preclinical drug discovery generates the highest expected returns of any stage in drug development.2 To optimally capture this extraordinary risk-reward, RS builds specialized staff and methods, crafts a unique class of large biology-themed investment portfolios, and prioritizes empirical strategies that increase the odds that the 650+ top biopharma acquirers will want to acquire a program early.

Specialist Teams & Processes

Large Structured Preclinical Portfolios

Early Exit Enablement

An Efficient New

Company Architecture

RS combines a novel decentralized team science model, portfolio-based R&D strategies, 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

Portfolio-Driven Synergies

Fully Virtual Operating Model

Centralized Technology Platforms to Maximize

R&D Advantages

RS continually curates, builds, and centralizes access to the most important new discovery, therapeutic, and translational technologies to maximize its companies' access to the most important new R&D technologies and their odds of efficient, successful, high quality drug discovery.

Curated R&D Partnerships

Discovery Technologies Platform

Therapeutic Technologies Platform

Clinical Translation Platform

Our Vision

All of biomedicine's stakeholders stand to benefit from improvements in biotech efficiency and success rates:

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.

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.

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.