Richard Murphey, 9/11/2018
In this series of short posts I'll touch on a few topics that you should think through when starting a company. I'll provide some examples of slides from pitch decks of successful companies that effectively communicate these topics.
Your development plan is not just an operational planning tool, but an important way for investors to assess your company's value, and your credibility as a manager.
I don't have a great example graphic for what this should look like yet, but a high level Gantt chart to summarize the plan is a good starting point. You can also include a Target Product Profile and summaries of the design of your planned experiments: what assay, test system or animal model are you using, what is the primary endpoint, what are the exploratory endpoints, what are your controls, is it randomized and blinded, where do the test articles and other reagents come from, who will perform the study, etc.
The plan should be realistic and very thoughtful. You should have a strong rationale for each item on the page. If you don't, be open about your uncertainty rather than guess (you can say, for example, you are targeting IND filing in 2H 2019, or even just 2019 -- if you aren't comfortable being more specific, don't be).
Investors look for very strong rationale for why you've chosen to do each study, as opposed to other studies you could do. The design of the study is also very important -- most good investors are good scientists, and they only fund good science.
Focus on "killer experiments" -- put your core hypotheses to the test, and try to kill them. As a founder, there can be a temptation to create an initial development plan with the goal of making progress as quickly as possible -- you don't have much money, and need to show progress to raise more. However, this approach is problematic, even if your experiments are well-designed and your conclusions are solid. The biggest risk for you as a founder is not that you spend 6 months working on something, it fails, and you can't get further funding, but that you spend 6 years working on something that fails, when you could have killed it far earlier without burning through significant capital (and potentially the most productive years of your career).
This plan should include both value-inflecting milestones (like experiments that show your product works) and the nuts-and-bolts items you'll need to take care of (tox studies, regulatory interactions, manufacturing scale up, IP). Including estimated costs to reach each milestone is also good, as long as you've done your homework and allowed a lot of cushion (things will take longer / cost more than you think).
Beyond establishing your credibility and thoughtfulness, your development plan should make it easy for investors to do the mental math to figure out whether 1) your company is a good investment and 2) this round is a good investment.
Series A investors will want a credible path to exit in 5-7 years. Usually that means some early clinical data showing your product works from an acceptably designed study (often Phase 1/2 or Phase 2). Your scientific advisory board and KOL calls should help you figure out what an "acceptably designed study" is for your product.
Investors will also want to clearly understand what value you will create with the current round. You don't have to get proof of concept in humans on your first round (although many Series A rounds are sized for this), but you do need to accomplish meaningful things: getting some tractable leads against your target, getting good data in a reliable animal model, completing IND-enabling studies, etc. Again, your SAB and KOL calls will help you figure out what milestones are best for your company at a given stage. Hopefully the feedback form on this tool will get you some VC feedback on milestones as well. Designing these initial human studies is very important, and the "clinical & unmet need" section deals with this.
Here you can include a more robust target product profile, and roadmap to getting that product made. Talk to physicians and read up on current treatments, as well as development stage treatments, to figure out what your product will need to look like to win in the market: what endpoints do doctors and patients care about, and what data will you need to convince physicians and patients to choose your product over others? Safety and effectiveness are key here, but don't ignore things like dosage form, frequency, route of administration, etc.
Once you know what your product needs to look like to get doctors to use it (and payers to pay for it), figure out the steps you need to take to get that your product to that point. What in vitro or animal models are representative of the endpoints you'd like to measure in humans? What assays will you need to develop to screen and improve compounds? What chemical matter will you need to produce? How much product will you need to manufacture at each stage? What will the FDA need to see? Who will do all this work?
Your SAB and KOL calls will help you answer those questions and refine your experimental design. It's important that you as a company get the design right before spending money on experiments. Launching early and failing fast doesn't work for wet lab experiments. It can take months and six figures to do an animal study at a CRO, and as an early-stage company, you probably won't survive more than one or two failed experiments. Investors will also focus on the design of your next few experiments, especially if you are a product company -- they're betting on an experiment, so they need to know what it looks like.
You also need a translational plan, especially if the animal models for your indication aren't great, you have a novel target or pathway, or there isn't much of a genetic link between your target and disease. The biggest component of the $2.5B cost to get a drug approved is the cost of Phase 2 failure: basically stuff that seems effective in animals and at the bench turns out to not work in humans. To address this risk, think about what biomarkers you can measure in vitro and in vivo that may correlate with human effectiveness. Are there genetic markers related to your target that correlate with relevant human phenotypes? Are there proteins that are strongly associated with clinical outcomes of interest, easily measurable (in blood), and that your product will impact? If you can measure these in your preclinical and early clinical (Phase 1) work, that can reduce your ultimate clinical risk.