Engineering Biotech 2.0
Related Sciences (RS) builds a new class of risk-optimized biotech companies and a unique suite of platform capabilities to design and efficiently manage them.
By re-envisioning every aspect of the biotech operating and investment model from the ground up, RS systematically mitigates the biggest historical sources of risk and inefficiency to create a new, better way to invest successfully in the discovery of important new medicines for patients.
Better Model Needed
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 Intrinsic Risk of Failure
Over 90% of all drugs fail in the clinic 1 and almost 85% of all biotechs fail to create any economic value. 2
Very Few Biotech Investors
99.7% of the world’s institutional investors have effectively zero exposure to therapeutics biotech. 3
Major Promise Left on the Table
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
Why is biotech so risky?
Risk in therapeutic development is fundamentally shaped by a discrete set of inter-related dimensions. RS spent years researching the top biotech operators and investors to elucidate the drivers of risk and inefficiency in biotech and the best ways to mitigate them.5
Poor Opportunity Selection
Biotech companies are often created to advance a specific area of research or technology, but without any form of objective comparison of that opportunity's risk-reward characteristics contextualized against others. As a result of this passive form of scientific bias, many companies unknowingly expose themselves to built-in risks that can materially reduce their long-term odds of success. For example, programs with strong human genetics evidence of links to a disease have historically achieved 3x+ higher rates of clinical success than those that do not, and structurally enabled targets with validated assays hold objectively greater odds of efficient, successful drug discovery than those without. Biotechs can increase their odds of success by prioritizing only those opportunities that benefit from superior objective characteristics which have historically predicted success, and avoiding those with features that empirically increase difficulty or failure risk.
Binary Outcomes
It is widely understood that the odds of clinical success in developing a new medicine are very low, with cumulative probabilities of failure before regulatory approval as high as 90-95%. However, faced with scarce resources, most biotech companies must opt to approach clinical development sequentially with a "lead asset" out in front and a small overall portfolio of clinical programs, creating high empirical probabilities of total loss. If biotech companies instead optimized for avoidance of bad binary failure risks, a range of alternate portfolio design, partnering, and exit strategies principles emerge which can help to improve overall risk-adjusted expected returns, by constraining certain traditional choices. From a decision theory perspective, several of these risk-optimization strategies also create a win-win outcome for both biotech and pharma, suggesting that new value creation paradigms in biotech are wholly possible.
Inefficient Company Designs
While each biotech focuses on a different research area, a significant portion of capital is often allocated to building very similar scientific and operating capabilities over and over again. From investing in core laboratory space and equipment, to recruiting generalist researchers, to all business development, accounting, and back office functions, and even including many types of common specialist advisors, a significant portion of most biotechs' investments are into fundamentally similar capabilities. As compared to models which better share capabilities or spread these investments across multiple companies, this default exposes biotechs to high fixed capital costs, rapid technology obsolescence risks, and material scalability constraints, while also creating negative economies of scale for the industry as a whole. Further, most biotechs continue to focus on local staffing within in "biotech hubs" instead of exploring newer models to overcome geographic constraints in engaging with the very best scientific talent. New innovations in company designs offer a range of stackable opportunities to enhance efficiency, flexibility, and scientific quality.
Insufficient R&D Capabilities
The therapeutics biotech sector benefits from broad and near-continuous cycles of technology innovation, as ever-improving drug discovery technologies, research tools, computational capabilities, and therapeutic modalities are invented and then quickly democratized. As a result, at any point in time, for virtually all biotechs, a range of important incremental advantages to their pace, costs, research goals, and/or overall odds of success, are likely on offer somewhere. For this reason, biotechs should increasingly focus on integrating a much wider range of technology advantages across many different aspects of the research, discovery, and development process, instead of purely focusing on building deep-narrow technology advantages. The availability and pace of technological change suggests the high value of adopting new hybrid internal-external or fully virtual R&D models powered by multiple external specialist vendors alongside, or even instead of, a sole reliance on internal capabilities and expertise.
An Innovative New Model
to Mitigate the Key Risks
RS combines innovations across four complementary areas to systematically mitigate biotech’s biggest historical sources of risk and efficiency and create of a new optimized class of therapeutics biotech company with superior risk-reward characteristics.
Opportunity Selection
RS FacetsTM is a unique, multilayered data science platform designed to ingest all activities in global biomedicine and enable RS to identify the top 0.001% of all opportunities on an unbiased, quantitative risk-reward basis.
RS Facets™️
Prioritization Engine
Time-Resolved Biomedical Atlas
Quantitative Opportunity Ranking
Predictive Machine Learning
Value Creation Strategy
The study of biotech's historical clinical and economic success and failure rates, contextualized against both its key risk inputs (capital and time) and reward outputs (returns on investment), suggests a set of evidence-based investment principles which can optimize a biotech's overall risk-adjusted expected returns while also minimizing its exposure to bad binary failure risks.
Preclinical Specialized
Portfolio-Based Discovery
Early Exit Optimization
Company Architecture
RS combines a novel decentralized scientific staffing model, a fully virtual operating model, synergy-optimized portfolio constructions, and asset-centric corporate structures, to significantly reduce costs and capital expenditure requirements while enhancing its companies' scientific depth, breadth, pace, and flexibility.
Decentralized Team Science
Data-Designed Portfolios
Fully Virtual Operating Model
Technology Advantages
RS continually builds and centralizes access to the latest discovery, therapeutic, and translational technologies to maximize its companies' odds of efficient, successful discovery of valuable new medicines.
Strategic 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.
Danger Bio focuses on danger detection—the “alarm system” inside of every cell which alerts the immune system to threats like infection and injury, and when imbalanced, can drive autoimmunity or cancers
Currently in design and assembly phase. Research focus not yet disclosed.
