We Build a New
Class of Biotech
Related Sciences (RS) utilizes a first-of-its-kind data science platform to identify the best new drug discovery opportunities on a quantitative basis, organizes them into large structured portfolios led by decentralized teams of top global scientists, and then operates them leanly over a shared central platform designed to maximize capital efficiency, technology advantages, and scientific quality.
By re-envisioning the biotech model from the ground up to take full advantage of the last decade's transformational innovations and insights, RS aims to create a new, better way to invest in the discovery of the drugs that are most likely to work.
Extraordinary Science Deserves a Fresh Model
The traditional biotech model’s poor risk profile drives high failure rates and constrains investment, slowing humanity’s pace of progress against all diseases.
High Historical Failure Rates
90-95% of all drugs fail in the clinic 1 and as a result, almost 85% of biotechs fail to create positive economic value. 2
Very Few Biotech Investors
99.7% of the world’s institutional investors have effectively zero exposure to therapeutics biotech, with only ~250 firms making 2+ therapeutics investments per year. 3
Slower Progress for Humanity
Over 75% of target-disease opportunities with strong evidence of links, have never been tried: 23,000+ opportunities spanning 3,800+ individual targets for 4,200+ diseases. 4
Revolutionary Biotech Design
The last decade's multi-disciplinary advances in genetics and biomedical data sets, R&D technologies and services, therapeutic modalities, AI and computation, and remote connectivity, collectively create an exciting menu of new possibilities to re-envision virtually all aspects of how a biotech is designed and operated to improve capital efficiency, scientific quality, and overall chances of success. RS spent years researching biotech's top operators and investors to map out these valuable new levers to improve biotech design. 5
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.
Valuable Advantages
Built Into Every RS Company
RS combines 12+ 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.
The Very Best Opportunities
Every new potential medicine comes with a range of important built-in characteristics that shape its unique risk-reward profile. How 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 machine learning platform designed to ingest all activities in global biomedicine and systematically predict the best new drug discovery opportunities for every human disease on an unbiased, quantified, explainable basis.
RS Facets™️
Prioritization Engine
All of Biomedicine in Data
Quantitative Opportunity Ranking
Predictive Machine Learning
Preclinical Drug Discovery
RS specializes in and builds its companies around preclinical drug discovery — the first 4-5 years of R&D during which a new drug is created and refined — because it generates the highest risk-adjusted returns of any stage in drug development. By being the best at just this one stage, and investing in the specialized R&D capabilities, partnerships, and expertise needed to enable world-class, hyper-efficient, multi-modality drug discovery, RS companies are uniquely positioned to discover the high-impact medicines the 600+ top biopharma acquirers value the most and acquire the most often.
Specialist Teams & Processes
Biology-Driven R&D Synergies
Early Exit Optimization
Company Architecture
RS combines a novel decentralized scientific staffing model, large scale program portfolios, a fully virtual operating model, and a tax-efficient and asset-centric corporate structure, to significantly reduce it companies' overhead costs and capital expenditure requirements while enhancing their R&D synergies, scientific depth, breadth, pace, and flexibility.
Decentralized Team Science
Large Structured Portfolios
Fully Virtual Operating Model
Technology Advantages
RS continually curates, builds, and centralizes access to the most important new discovery, therapeutic, and translational technologies to maximize its companies' odds of efficient, successful, high quality drug discovery. By blending internal capability-building with external strategic partnerships and vendor curation, RS seeks to maximize its cost and capital efficiency, program scalability, and overall breadth of access to new R&D technologies.
Strategic R&D Partnerships
Discovery Technologies Platform
Therapeutic Technologies Platform
Clinical Translation Platform
A better biotech model
benefits everybody
Biotech's overall success and efficiency rates directly determine the new medicines humanity is able to benefit from. As such, all of biomedicine's stakeholders can benefit from improvements in biotech's operating and investment model that increase its successful shots on goal or reduce its time- talent- and financial- waste along the way:
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.
Companies
RS builds, launches, and manages one new company 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.
