Our story

About BioDrive Cycling

BioDrive began with a deceptively simple question.

The 2022 Mathematical Competition in Modeling challenged teams to determine how an Individual Time Trial cyclist should pace a race given their unique power profile. To Applied and Industrial Mathematics student Cora Laurie (then McFarlane), the problem was immediately familiar. Having previously trained extensively for triathlon, she understood that pacing was far more than a mathematical exercise—it was a challenge that every endurance athlete faces. Combined with her longstanding interest in physics and human performance, the problem represented the perfect intersection of her passions.

Cora and her teammates successfully completed the 96-hour competition, but the question refused to stay solved. When later given the opportunity to choose her own master's thesis topic, she returned to the same problem.

The resulting graduate research developed and compared two mathematical approaches for determining the minimum achievable race time while accounting for an athlete's energy availability and instantaneous power limitations. The methods were then used to generate and compare optimal pacing strategies across different athlete profiles.

Yet as discussions with interdisciplinary colleagues continued, one conclusion became increasingly clear: the mathematics was only part of the solution.

What good was an "optimal" pacing strategy if an athlete had to ride exactly watt-for-watt as the algorithm predicted? How could a cyclist trust recommendations without understanding where they came from? And how could any athlete realistically remember and execute thousands of data points during competition?

The challenge was no longer finding the best strategy. It was translating complex optimization into guidance that athletes and coaches could confidently understand and apply.

From that realization, BioDrive was born.

The realism of an optimizer. The explainability of physiology. The transparency of a human coach.

Our goal has never been to replace the coach. Instead, we aim to combine the strengths of mathematical optimization with the experience, intuition, and communication that only a coach can provide.

The optimization methods developed through this research generate race strategies tailored to each athlete, each course, and each set of race conditions. Rather than relying on general heuristics or one-size-fits-all pacing advice, BioDrive models the physics of the course itself, evaluating how every metre affects the rider and how every decision influences the remainder of the race.

At the heart of this approach is a digital twin of the athlete: a computational model that represents their physical characteristics, power profile, and physiological response to exercise. By racing this digital athlete through a virtual version of the course, BioDrive can evaluate not only how quickly a strategy completes the course, but how the athlete's body responds throughout the effort. As the platform evolves, this model will expand to include additional physiological factors such as fueling strategy.

While our optimization engine provides the analysis, we believe the final strategy should always remain a conversation between athlete and coach. To address the critical human element of this very human problem, BioDrive partners with coaches who are trained to leverage our tools effectively. These coaching partners translate our analyses into practical, personalized race plans that reflect both the data and the athlete standing in front of them. Our work is strengthened by their expertise and could not exist without it.

At present, BioDrive focuses on non-drafting endurance events, such as Individual Time Trials and triathlons, where an athlete's pacing decisions are primarily their own. Future development will extend these methods to drafting disciplines, incorporating the strategic interactions between riders that make pack racing such a rich and challenging optimization problem.

The team

The BioDrive team brings together expertise in mathematical modelling, software development, research, and business operations.

We also gratefully acknowledge the support of Ontario Tech University's Brilliant Catalyst team, whose encouragement and guidance were invaluable during BioDrive's earliest stages.

Looking ahead

BioDrive's long-term vision extends well beyond pre-race pacing plans. Future projects include live in-race strategy correction, high-fidelity race simulation and training, and the expansion of our modelling framework into additional endurance sports. Our mission remains the same as it was when this journey began: to make sophisticated optimization understandable, actionable, and genuinely useful for the athletes and coaches who rely on it.