Revolutionize Drug Discovery with Recursion OS

Table of Contents

1. Introduction
2. The Recursion OS: What is it?
   1. Definition and Purpose of the Recursion OS
   2. How it Works: Tools and Processes
   3. The Importance of Data in the Recursion OS
      1. Scale
      2. Reliability
      3. Relatability
3. The Recursion Mindset: Thinking Beyond Traditional Approaches
   1. Traditional vs. Recursion Approach to Drug Discovery
   2. The Power of Data as Fuel
   3. The Value of Connected Data
4. The Phonomics Layer: Unbiased Study of Cellular Morphology
   1. Introduction to the Phonomics Layer
   2. Experimental Mapping of Biological and Chemical Relationships
   3. Mining Data for Actionable Insights
5. The Transcriptomics Layer: High-Dimensional Study of Gene Expression
   1. Adding Transcriptomics to the Data Layer
   2. Running Multi-Well Plate Experiments for Efficient Analysis
   3. Extracting Insights for Hit-to-Lead Activities
6. The Invivomics Layer: High-Temporal Resolution Animal Studies
   1. Introduction to Invivomics
   2. Advantages of Digital Animal Studies
   3. Applications in Disease Induction, Tolerability, and Liability Studies
7. Integrating Chemistry into the Recursion OS
   1. Advancements in Design and Analysis
      1. Multi-Objective Generative Chemistry
      2. Molecular Foundation Model for Drug Discovery
   2. Advancements in Physical and Robotic Operations
      1. Automated DMPK testing Facility
      2. Automated Microsynthesis Systems
   3. The Role of Active Learning in Optimizing Molecule Selection
8. Conclusion

The Recursion OS: Revolutionizing Drug Discovery with Data

Drug discovery is a complex and time-consuming process that often relies on trial and error, limited data sets, and a narrow focus on specific hypotheses. But what if there was a different approach? An approach that leveraged the power of big data, machine learning, and an unbiased exploration of biology and chemistry? That's where the Recursion OS comes in.

Introduction

The Recursion OS is the culmination of years of research and development at Recursion, a leading biotech company focused on industrializing drug discovery. It is a scientific and technical platform that combines tools, processes, and data to enable the rapid and efficient discovery of Novel drugs. In this article, we will explore the various aspects of the Recursion OS and its impact on the field of drug discovery.

The Recursion OS: What is it?

Definition and Purpose of the Recursion OS

At its core, the Recursion OS is a comprehensive set of tools and processes created to build and interrogate massive data sets in biology and chemistry. It is the result of the collective work of hundreds of Recursion scientists over the past decade. The main purpose of the Recursion OS is to industrialize drug discovery, decode biology, and ultimately accelerate the development of new drugs for patients.

How it Works: Tools and Processes

The Recursion OS encompasses a wide range of tools and processes that enable the efficient exploration and analysis of biological and chemical relationships. One key component of the Recursion OS is the phonomics platform, which allows for the unbiased study of the morphology of cells. Through the phonomics platform, Recursion scientists have charted trillions of biological and chemical relationships that can be mined for actionable insights.

The Recursion OS also encompasses the use of transcriptomics, which is the high-dimensional study of gene expression. By layering transcriptomic data onto the phonomics platform, Recursion scientists gain a deeper understanding of cellular behavior and can identify promising compounds for further development.

Another critical aspect of the Recursion OS is the invivomics layer, which involves high-temporal resolution animal studies. This layer allows for the observation and analysis of animal behavior and physiological responses to compounds, providing valuable insights into efficacy, tolerability, and liability.

The Importance of Data in the Recursion OS

Scale

One of the defining features of the Recursion OS is the scale of data it can generate and analyze. With the ability to produce trillions of biological and chemical relationships, Recursion has built a massive proprietary data set, totaling over 21 petabytes. This scale of data not only allows for a comprehensive understanding of biology but also enables the identification of subtle Patterns and relationships that might have otherwise been missed.

Reliability

In addition to scale, the Recursion OS places a strong emphasis on the reliability of the data generated. Through stringent quality control measures and standardized experimental protocols, Recursion ensures that the data collected is accurate and reproducible. This reliability is crucial in drug discovery, where confidence in the data is essential for making informed decisions about which compounds to pursue.

Relatability

The final dimension of data in the Recursion OS is relatability. The ability to connect data across different layers and programs is a key advantage of the Recursion OS. By integrating data from phonomics, transcriptomics, and invivomics, Recursion scientists can gain a comprehensive view of biological and chemical relationships, leading to novel and actionable insights. This relatability also allows for efficient and targeted experimental design, saving both time and resources.

The Recursion Mindset: Thinking Beyond Traditional Approaches

Traditional vs. Recursion Approach to Drug Discovery

In traditional drug discovery approaches, the focus is often on narrow hypotheses and bespoke assays. This can lead to a limited exploration of biology and chemistry, as well as a high risk of failure if the initial hypothesis proves to be incorrect. In contrast, the Recursion OS takes an unbiased and target-agnostic approach to drug discovery. By looking at large swaths of biology and chemistry simultaneously, Recursion can uncover unexpected insights and overcome biases inherent in the literature.

The Power of Data as Fuel

Central to the Recursion mindset is the understanding that data is not merely an exhaust or a byproduct of the drug discovery process. Instead, data is seen as the fuel that drives every hypothesis and program forward. By using their in-house data for every hypothesis and every program, Recursion scientists can leverage the power of data to Ignite and accelerate their drug discovery efforts. This data-driven approach increases confidence, allows for the discovery of unexpected insights, and creates a competitive advantage that grows stronger over time.

The Value of Connected Data

In traditional drug discovery approaches, data is often siloed within individual programs, limiting the ability to compare and learn from different experiments. This fragmented approach impedes the efficiency and efficacy of drug discovery efforts. In contrast, the Recursion OS connects data across programs and over time, creating a cumulative portfolio that can be pushed forward with a unified research infrastructure. This connected data enables Recursion to rapidly learn what works and what doesn't, deploy changes across the organization, and continuously improve their drug discovery process.

The Phonomics Layer: Unbiased Study of Cellular Morphology

Introduction to the Phonomics Layer

One of the key data layers in the Recursion OS is phonomics, which involves the unbiased study of the morphology of cells. Through the phonomics platform, Recursion scientists can analyze the physical characteristics of cells and identify patterns and relationships that may be Relevant to drug discovery. This data layer provides a wealth of information about cellular behavior and helps guide the selection of promising compounds for further study.

Experimental Mapping of Biological and Chemical Relationships

The phonomics layer relies on the physical mapping of biological and chemical relationships. By Charting trillions of such relationships, Recursion scientists can create a comprehensive map of biology and chemistry. This map serves as a valuable resource for mining actionable insights and identifying novel targets and pathways for drug discovery.

Mining Data for Actionable Insights

The value of the phonomics layer lies in its ability to provide insights that can guide drug discovery efforts. By applying machine learning algorithms to the phonomics data, Recursion scientists can detect and differentiate between healthy and diseased cellular states, identify potential drug targets, and assess the efficacy of compounds. This data-driven approach increases the efficiency and success rate of drug discovery programs and allows for more informed decision-making.

The Transcriptomics Layer: High-Dimensional Study of Gene Expression

Adding Transcriptomics to the Data Layer

In addition to the phonomics layer, Recursion incorporates transcriptomics into its data layer. Transcriptomics is the high-dimensional study of gene expression, which provides valuable information about the activity and regulation of genes. By layering transcriptomic data onto the phonomics platform, Recursion scientists can gain a deeper understanding of cellular behavior and identify potential targets for drug development.

Running Multi-Well Plate Experiments for Efficient Analysis

Traditionally, transcriptomics experiments are performed sample by sample, which can be time-consuming and expensive. However, Recursion has developed a robotic version of transcriptomics using multi-well plates, allowing for the simultaneous analysis of hundreds of compounds. This high-throughput approach enables Recursion scientists to generate dense and connected data layers, leading to more accurate and actionable insights.

Extracting Insights for Hit-to-Lead Activities

By analyzing the transcriptomic data in conjunction with other layers of data, Recursion scientists can extract valuable insights for hit-to-lead activities. This includes selecting the most promising compounds for further optimization and understanding their mechanisms of action. The integration of transcriptomics into the Recursion OS enhances the efficiency and success of drug discovery programs by providing a deeper understanding of gene regulation and its impact on cellular behavior.

The Invivomics Layer: High-Temporal Resolution Animal Studies

Introduction to Invivomics

The invivomics layer of the Recursion OS involves high-temporal resolution animal studies. This layer allows for the observation and analysis of animal behavior and physiological responses to compounds, providing valuable insights into the efficacy, tolerability, and liability of potential drug candidates. By incorporating animal studies into the data layer, Recursion can bridge the gap between in vitro and in vivo experimentation and gain a more comprehensive understanding of drug effects.

Advantages of Digital Animal Studies

Digital animal studies, enabled by high-temporal resolution video monitoring, offer several advantages over traditional approaches. By capturing continuous video footage of animal behavior in their original cages, Recursion scientists can obtain unbiased and detailed data on the effects of compounds. This approach eliminates the confounding factors associated with manual handling and allows for the detection of subtle changes in behavior that may indicate efficacy or toxicity. Furthermore, digital animal studies enable real-time monitoring and analysis, reducing the time required to assess compound effects and accelerating the drug discovery process.

Applications in Disease Induction, Tolerability, and Liability Studies

The invivomics layer is instrumental in studying various aspects of drug development, including disease induction, tolerability, and liability. By exposing animals to compounds and analyzing their behavioral and physiological responses, Recursion scientists can validate disease models, assess the tolerability of potential drug candidates, and evaluate their potential liabilities. This comprehensive approach provides crucial information for decision-making in drug discovery and ensures the safety and efficacy of potential drug candidates.

Integrating Chemistry into the Recursion OS

The Recursion OS is not limited to biological data but also integrates chemistry into its framework. By combining digital and robotic operations in chemistry, Recursion aims to reduce the time and cost required for each cycle of the drug discovery process.

Advancements in Design and Analysis

Recursion has made significant advancements in both the design and analysis phases of the drug discovery process. Through multi-objective generative chemistry, Recursion scientists can optimize multiple parameters and design molecules with desired properties. The molecular foundation model for drug discovery enables efficient prediction of compound properties from limited data points, improving the decision-making process and maximizing the value of available data.

Advancements in Physical and Robotic Operations

Recursion has also invested in automating physical and robotic operations in chemistry. The establishment of an automated DMPK (distribution, metabolism, excretion, and toxicity) testing facility enables the rapid assessment of hundreds of molecules per week, providing critical data for optimizing compound properties and safety. Additionally, the development of automated microsynthesis systems allows for the efficient synthesis of new molecules, further expanding the exploration of chemical space.

The Role of Active Learning in Optimizing Molecule Selection

Active learning is a key component of the Recursion OS, allowing algorithms to select the most promising molecules for testing based on available data. The integration of active learning with the extensive data layers in the Recursion OS enhances the efficiency of the drug discovery process by prioritizing compounds with the highest likelihood of success. This iterative approach reduces the number of cycles required to reach candidate selection and maximizes the chances of identifying novel and effective drugs.

Conclusion

The Recursion OS represents a paradigm shift in drug discovery, leveraging an unprecedented wealth of data, machine learning algorithms, and a comprehensive understanding of biology and chemistry. By combining phonomics, transcriptomics, invivomics, and chemistry, Recursion scientists can efficiently explore and analyze complex biological and chemical relationships, leading to the discovery of novel drugs for patients faster than ever before. The Recursion OS is a testament to the power of data-driven approaches in revolutionizing the field of drug discovery and improving human health.

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