Better Medicine, Fast — Why We Invested in Intrepid Labs
TL;DR: Propagator Ventures has invested in Intrepid Labs, a Canadian startup that combines machine learning, robotics, and pharmaceutical science to speed up drug development. Founded in 2023 and spun out of the University of Toronto (U of T), Intrepid Labs addresses the bottlenecks in drug formulation, which is often slow, costly, and labour-intensive. The cross-disciplinary team at Intrepid Labs includes deep domain expertise in AI, robotics, and drug formulation science. Intrepid’s technology can reduce drug development timelines, unlock new therapies, enable personalised medicine, and lower clinical failures. Propagator Ventures sees Intrepid Labs’ self-driving labs as the future of drug development, creating life-saving therapies while cutting costs and attrition rates.
Integrating machine learning, robotics, and pharmaceutical science to fast track the future of drug development.
Our recent investment in Intrepid Labs marks our first foray into the emerging field of drug formulation driven by machine learning and aligns with our strategy to back transformative deep-technologies and world-class teams tackling grand global challenges. We are excited to partner with Intrepid’s visionary founders and join Radical Ventures as ambitious first backers of Intrepid Labs in Canada.
Rooted in Pioneering Research
Intrepid Labs spun out of U of T in 2023 to commercialise ground-breaking medical innovation stemming from the labs of leading researchers in machine learning, robotics, and drug formulation science. Intrepid is the first company to emanate from the Acceleration Consortium (AC), an institutional strategic initiative based at U of T, set up to accelerate the design and discovery of new functional materials using self-driving laboratories powered by AI. The Consortium is led by Intrepid Labs co-founder, Prof. Alán Aspuru-Guzik.
The Formulation Bottleneck
While the pharmaceutical industry has seen incredible advances in drug discovery over the past few decades, a critical bottleneck remains — converting promising new therapeutic compounds into viable medical products that can be safely administered to patients. After a new drug candidate is identified through the discovery process, a formulation needs to be developed for further pre-clinical and clinical evaluation.
Formulation development is typically a time-consuming and labour-intensive process that is largely reliant on benchmarking against existing formulations and trial and error experimentation. As a result, companies often settle on a formulation that is “good enough”. But with over 90% of drug candidates failing due to efficacy or toxicity issues, this conventional approach limits our ability to unlock the full therapeutic potential of new drug molecules.
Intrepid’s AI-Driven Formulation Platform
Intrepid Labs is pioneering a radical solution — a self-driving laboratory that combines AI, robotics, and high-throughput experimentation to autonomously optimise drug formulations. Their proprietary platform — called VALIANT— takes a data-driven approach that employs advanced machine learning and robotic automation to efficiently explore the large formulation design space and identify the optimal formulation for a specific drug. Intrepid’s data-driven approach aims to turn this high-dimensional challenge into a rapid optimisation problem.
A Platform for Intelligent Drug Design
VALIANT rapidly prepares and tests a wide array of candidates in parallel, using the results to iteratively refine its machine learning models and zero in on optimal compositions. This closed-loop system explores the design space orders of magnitude faster than conventional methods, using much less resources, identifying viable formulations for even highly challenging drug molecules.
The “build-test-learn” cycle, powered by proprietary machine learning models and wet lab automation, enables Intrepid to search a significantly larger formulation space and surface non-obvious solutions that may elude other drug developers. Crucially, VALIANT is modular and can optimise formulations based on various drug delivery technologies, and moreover it has the capability to discover entirely new drug delivery technologies. The platform has already demonstrated the ability to rescue failed compounds and rapidly optimise long acting injectables, oral solid dosage forms, and nanoparticle formulations for small molecules and biologics. This flexibility across therapeutic areas and product types provides multiple shots on goal.
Intrepid Labs’ deep scientific foundation, augmented by a robust IP portfolio, provides the company with an unparalleled technological edge in tackling the formulation bottleneck that constrains the pace and economics of drug development.
Team and Ecosystem
Beyond its computational capabilities, Intrepid’s edge lies in its cross-disciplinary team with deep domain expertise at the intersection of AI, robotics, drug formulation & development. Prof. Christine Allen is a world-renowned entrepreneur and merited drug formulation and development scientist, with more than 170 publications. Her co-founders include Prof. Alán Aspuru-Guzik, a serial company founder and internationally recognised pioneer at the interface of quantum information, machine learning and chemistry. The founding team also includes Dr. Pauric Bannigan, an accomplished drug formulation scientist and inventor with extensive experience in the development of innovative drug delivery platforms, and Dr. Riley Hickman, an expert in materials discovery, applied mathematics, machine learning and robotics.
With decades of experience and domain expertise, connections across industry and stellar academic and commercial pedigrees this team has the perfect credentials to bridge the gap between bits and molecules and to realise the immense potential of their self-driving lab technology. As a resident of the Johnson & Johnson Innovation — JLABS incubator in Toronto and member of the Vector Institute’s FastLane Program Intrepid Labs is also set to benefit from its robust position in the vibrant Canadian tech ecosystem.
Accelerating Medicines that Matter
The ability to optimise drug products with unprecedented speed and scale opens up significant opportunities for Intrepid across the $1.4T pharma value chain. When successful, their platform could:
● Dramatically shrink drug development timelines by rapidly optimising formulations for solubility, stability, and bioavailability.
● Unlock new therapeutic modalities by rescuing promising drug candidates previously abandoned due to poor pharmacokinetics.
● Facilitate personalised and precision medicine by tailoring formulations to specific patient populations.
● Reduce clinical failures by prioritising formulation optimization earlier in development.
● Extend patent life and create new revenue streams by reformulating existing drugs.
● Reduce complexity and cost of existing drug product development and manufacturing while maintaining performance.
The global pharmaceutical industry is steadily growing; even capturing a fraction by effectively streamlining the formulation dimension could be transformative for Intrepid Labs. Not only is their technology highly scalable — it can begin formulation optimization without any initial data points and learn through experience. This capability allows for the inclusion of the newest classes of therapeutic agents and eliminates the need for large datasets to deploy ML models. In a world with growing data security concerns, this provides a powerful competitive advantage.
The Opportunity Ahead
By making drug formulation more of a data-driven engineering problem than an artisanal process, Intrepid has the potential to reshape how medicines are designed, tested and delivered. While early, Intrepid is pioneering an emerging paradigm — applying machine learning, robotics, and autonomous systems to accelerate not only drug discovery, but the entire drug development pipeline.
Intrepid Labs’ initial formulation focus tackles a key bottleneck, but their vision is grander: The potential for reducing the need for time consuming and costly experimental studies by applying machine learning models to accelerate the design of long-acting injectables was described in a study published in Nature Communications last year; one of the first to apply machine learning techniques to the design of polymeric long-acting injectable drug formulations.
We believe Intrepid’s self-driving labs represent the future of drug development, much like how AI is accelerating design cycles in materials, semiconductors and other complex product categories.
At its core, Intrepid is tackling one of healthcare’s most valuable challenges — accelerating the development of life-saving therapies while reducing costs and attrition rates. We at Propagator Ventures are excited to support Intrepid in ushering in a new era of programmable, intelligent drug design — where the pace of medicine is no longer limited by trial and error but accelerated by algorithms and automation. The opportunity to reduce the time and cost associated with formulation development by a factor of 10 is a game-changer not just for the industry but for patients everywhere.
Disclaimer: This article has been edited by an AI model, but the content is original and was generated by human authors.
