The case for scientific PMs

At Kaleidoscope, we've collaborated with many types of project and program managers. Over time, we've found ourselves particularly drawn to working with scientific PMs – those who combine deep technical understanding with operational leadership. Through these collaborations, we've observed how scientific PMs enable a distinct operating model in biotech programs.

Modern biotech programs are networks of interdependent decisions. Each choice cascades through multiple domains: technical, operational, and strategic. A seemingly straightforward decision about analytical method validation can affect everything from manufacturing scale-up to clinical timeline feasibility. A choice about which assays to prioritize shapes both near-term resourcing and long-term clinical strategy. Managing projects is uniquely challenging in biotech compared to other domains.

The traditional way to handle this complexity is to split responsibility: scientists make technical decisions, program managers handle operational impact, and leadership reconciles the two. This model made sense when biotech programs were simpler and more linear. You could generally separate technical and operational decisions because their interactions were more limited and predictable.

But three major shifts have made this model increasingly ineffective. First, modern therapeutic modalities are far more complex, with more intricate manufacturing processes and analytical requirements. Second, regulatory pathways have become more sophisticated, offering more options but requiring more strategic navigation. Third, the pressure to optimize capital efficiency means companies need to make better decisions faster.

Many companies try to adapt by having scientists spend part of their time on program management. The logic seems sound: Who better to manage technical decisions than someone who understands the science? But this creates a different problem. Program management in modern biotech isn't a part-time job. It requires dedicated focus to track and manage all the moving pieces. A scientist splitting their time will inevitably focus more on their scientific responsibilities, treating program management as secondary, which can be hugely costly for the company (we've talked before about the importance of biotechs promoting operational excellence).

Other companies bring in experienced program managers without any scientific backgrounds. This might work better in terms of operational excellence, but creates a persistent translation tax. Every technical decision requires multiple meetings to explain implications. Program managers have to constantly validate their understanding with technical teams. And because they can't independently evaluate technical risks, they often miss early warning signs that could have prevented later issues.

Scientific PMs offer a fundamentally different model. Rather than trying to coordinate between technical and operational tracks, they integrate them from the start. This changes how programs actually run in several specific ways.

First, it changes how decisions get made. Instead of sequential evaluation (technical team considers scientific merit, then program team considers operational impact), you get integrated assessment. A scientific PM can simultaneously evaluate whether an analytical method is technically sound and whether it's operationally feasible at scale.

Second, it changes risk identification and management. Traditional PMs spot operational risks like timeline delays or resource constraints. Technical teams spot scientific risks like assay reliability or process robustness. But many critical risks live at the intersection – like whether a technically valid but complex assay will be reliable enough for lot release testing. Scientific PMs can spot these hybrid risks early because they understand both domains.

Third, it changes how teams operate. When your program leader truly understands both science and operations, teams spend less time explaining and more time solving problems. Technical discussions naturally include operational considerations. Operational planning naturally accounts for technical complexity.

This model requires a specific type of leader. You need someone with enough scientific depth to understand technical tradeoffs, but who also excels at operational leadership. They need to be technical enough to engage meaningfully with scientists, but focused on driving programs rather than doing science. Finding people with this combination isn't easy, but it's worth the effort.

The implications vary based on company context. Early-stage companies benefit most from scientific PMs who understand how technical decisions shape future operational requirements. Platform companies need PMs who can navigate the complex interactions between platform development and individual programs. Later-stage companies need PMs who can manage the increasing complexity of clinical development while maintaining strong connection to technical fundamentals.

But across all contexts, the key is treating these roles as what they are: strategic leadership positions that require both scientific depth and operational excellence. Not scientists doing PM work on the side, or an Ops person constantly having to tap scientists’ shoulders to clarify a technical question. 

Modern biotech is complex, with many ways to run programs effectively. From our experience, scientific PMs create a distinct operating model – one where decisions don't need multiple rounds of translation between technical and operational considerations. When programs integrate these perspectives from day one, they can move more efficiently. It's worth considering where these roles might fit in your organization, not because they're better or worse, but because they offer a different way to tackle the challenges of bringing promising science to patients.

Kaleidoscope is a software platform for biotechs to robustly manage their R&D operations. With Kaleidoscope, teams can plan, monitor, and de-risk their programs with confidence, ensuring that they hit key milestones on time and on budget. By connecting projects, critical decisions, and underlying data in one spot, Kaleidoscope enables biotech start-ups to save months each year in their path to market.