Evidence Roadmaps Made Simple

This blog post picks up from the first post: “Turning Early Funding Into Evidence and Impact” and expands on the Plan step of the PGDIPS framework that we introduced. To make this step more tangible, we’ll follow a fictional startup while it navigates early planning decisions that every innovator eventually faces as we invite you to “Choose your Next Move”.

Early funding comes with momentum; and pressure. One of the first questions founders face is: how do we design an evidence plan that keeps us on track without drowning us in complexity?

At Imara Strategic Advisors, we’ve seen startups fall into two traps: overbuilding evidence strategies that stall progress, or under-planning and paying the price later with costly delays or pivots. The sweet spot is a fit-for-purpose roadmap: structured enough to guide decisions, but lean enough to stay flexible.

Without a clear roadmap, teams often either:
- Spin their wheels in endless study design discussions, or
- Rush forward collecting data that doesn’t align with regulatory, payer, or market needs.

Both paths waste precious time and funding. Your early-stage evidence plan should help you move forward confidently while leaving space to adapt. In this blog post, we highlight a series of actionable steps that you can take when designing your roadmap.

1. Anchor Your Roadmap in Endpoints That Matter
Start with your long-term goals: regulatory clearance or approval, payer adoption, and clinical uptake, retail shelf space/ over-the-counter. Backward plan from these endpoints so that today’s decisions build toward tomorrow’s goals.

2. Define “Minimum Viable Evidence”
Ask yourself: what’s the least amount of evidence needed to reach the next milestone (Series B, FDA submission, or partner engagement)? This keeps you from collecting “nice-to-have” data that drains resources.

3. Integrate Regulatory, Clinical, and Commercial Inputs
Evidence isn’t just for regulators. Build a plan that also answers investor, payer, consumer and clinician questions. This cross-functional approach ensures alignment and avoids siloed decisions.

4. Build in Flexibility, Not Rigidity
Your first evidence roadmap shouldn’t lock you into a single path. Design with checkpoints where you can pivot based on results, feedback, or market shifts.

Choose Your Next Move: The Planning Dilemma

NeuroPath Diagnostics has just closed its first funding round. Their AI-based biomarker test shows promise, and the team is eager to move fast. With investors asking for momentum and partners requesting data, they meet to decide how to plan their evidence strategy.

Option A:
The CEO proposes launching several small pilot studies in parallel-one with a hospital partner, another with a lab collaborator- to show momentum and attract Series B interest.

Option B:
The Head of R&D suggests focusing on a single, tightly scoped feasibility study to confirm the assay’s performance and refine endpoints before expanding into multiple sites.

Option C:
The team’s business advisor advises waiting for additional payer and customer input before investing in any new studies, arguing that market validation should drive the evidence plan.

After hours of discussion, they choose to begin with a single, well-scoped feasibility study. It’s not the flashiest path, but it builds clarity and confidence across the team.

The takeaway: effective planning isn’t about doing the most; it’s about doing the right next thing and avoiding common pitfalls. A focused roadmap gives clarity without rigidity- guiding evidence generation with purpose.

Common Pitfalls in the absence of an evidence roadmap

i) Mistaking more data for better data:

As we cautioned in our previous blog post- the key isn’t to collect everything, it’s to collect what matters most

ii) Overcomplicating with multiple parallel studies before proof of concept is clear:

One of the most common missteps we see among early-stage innovators is the urge to “do it all” at once; launching multiple studies in parallel before confirming proof of concept. While the intention is often good (to move fast or show momentum), this approach can quickly backfire. Running concurrent studies spreads limited resources thin, both financially and operationally, and often yields data that is fragmented or premature.

 At this stage, your goal isn’t to validate everything- it’s to validate the right things. A single, well-designed proof-of-concept or feasibility study provides the foundation upon which later, more specialized studies can build. Without that anchor, parallel efforts risk generating conflicting results, creating confusion for investors and regulators, and delaying your path to a clear narrative. 

The takeaway: early-stage evidence generation should be sequential, not simultaneous. Confirm your core concept first- technical performance, usability, or clinical relevance-then layer in more complex or comparative studies. A focused approach builds confidence, keeps your burn rate in check, and gives your evidence roadmap structure and momentum.

iii) Ignoring payer and market evidence needs until late in the game:

Many startups design their early evidence plans solely around regulatory approval, assuming payer and market access considerations can come later. But in today’s environment, regulatory clearance alone doesn’t guarantee adoption. Payers, providers, and even customers increasingly expect data that demonstrates clinical utility, cost-effectiveness, and real-world relevance. When these needs are overlooked until late in the process, companies often find themselves redoing studies or generating new data to satisfy reimbursement or procurement requirements-an expensive and time-consuming setback.

Integrating payer and market perspectives early ensures that your evidence plan is future-ready. This doesn’t mean conducting full health economics or outcomes research from day one, but rather identifying what evidence questions those audiences will eventually ask. For example: Does this innovation reduce downstream costs? Does it improve diagnostic speed or accuracy in a way that matters to clinicians? How does it fit into existing care pathways?

By considering these questions during the planning phase, you can build studies that serve multiple stakeholders at once; regulators, investors, and payers-without duplicating effort later. Ignoring these perspectives may get you to approval faster, but it rarely gets you to adoption faster.

iv) Failing to revisit and revise the roadmap as new information emerges:

A common trap for early-stage companies is treating the evidence roadmap as a fixed plan rather than a living framework. The reality is that science, strategy, and context evolve quickly- new data, regulatory feedback, or even competitor moves can shift the landscape overnight. When teams fail to revisit their roadmap, they risk following a plan that no longer reflects their current priorities or opportunities. What started as a clear direction can become a constraint.

Effective evidence roadmaps are designed for iteration. Regular checkpoints; after key experiments, investor updates, or regulatory interactions; allow teams to refine assumptions, recalibrate timelines, and re-sequence studies based on what they’ve learned. Even small updates, like adjusting an endpoint or adding a usability component, can have an outsized impact on readiness and efficiency.

Building flexibility into your roadmap from the beginning helps make revision a normal part of execution, not an emergency response. The goal isn’t to constantly rewrite your plan, rather it’s to maintain alignment between what you know now and where you’re headed. Teams that embrace this adaptive mindset are better positioned to respond to unexpected findings, optimize resources, and sustain momentum toward commercialization.

How Imara Can Help

At Imara, we know how easy it is for early-stage teams to get pulled in too many directions. Our job is to help you bring focus back to what really matters; building a roadmap that’s smart, strategic, and right-sized for where you are.

We work with innovators to design fit-for-purpose regulatory and evidence roadmaps that balance rigor with agility. Think of it as a plan that’s solid enough to earn investor and regulator confidence, but flexible enough to evolve as your data and strategy mature.

Together, we’ll help you:

• Identify the milestones that truly drive your next stage of growth

• Align your evidence plans with the expectations of investors, regulators, and key stakeholders

• Avoid spending time and resources on studies that don’t move your strategy forward

Our goal is simple: to give you clarity without the clutter; so you can move faster, spend smarter, and build lasting momentum toward market success.

To wrap up this post, let’s revisit the consequences of the 3 options that our fictional startup, NeuroPath Diagnostics considered:

• If you chose Option A, NeuroPath looks busy but spreads its resources too thin. The studies generate inconsistent data and leave the team with more questions than answers.

• If you chose Option B, the focused feasibility study provides clear proof-of-concept data and helps shape a stronger, right-sized roadmap for growth.

• If you chose Option C, the delay soothes short-term risk but frustrates investors and slows technical progress; the company loses early momentum.