Driving commercial success in biopharma: in conversation with Paul Sekhri

What does it take to effectively commercialize a drug? How can biotech leaders successfully navigate this long, winding, and expensive road, especially at a time when market pressures demand precise execution and focus? We recently spoke about this with biopharma veteran, Paul Sekhri. Synopsis and recording below.

Paul Sekhri is President and CEO of vTv Therapeutics, a clinical stage biotechnology company. Prior to vTv, Paul was CEO of numerous biotech companies, such as eGenesis, Lycera, and Cerimon, among others. He has also held senior roles across major companies like Sanofi (Senior Vice President, Integrated Care), Novartis (Senior Vice President and Head, Global Search and Evaluation and M&A), TPG Biotech (Operating Partner and Head of Biotech Ops). Overall, Paul has been a Director on more than 35 private, public company, and non-profit Boards, and has leveraged his many decades of experience to help biotechnology companies get cutting-edge drugs to the patients who need them.

So much goes into discovering and commercializing a new drug. This decades-long endeavor is notorious for high costs and high failure; add on difficult market conditions, and you're left with an extremely challenging environment for companies navigating the space. Yet biotechnology is a crucial industry, powering strides in advancing human and planetary health. Given this, how can teams innovating in the field maximize their chance of success? Recently, Bogdan (Co-Founder & CEO, Kaleidoscope) sat down with Paul Sekhri to discuss.

Summary points

• Work back from the ideal target product profile needed at launch. Being too heads-down on the science immediately in front of you can lead to existentially-threatening moments years down the line.
• Kill preclinical programs early. Dragging too many weak programs forward into clinic is a drain on precious resources and hurts your chances of success on the other side.
• Build real competitive advantage by using data to drive decisions. It doesn't stop with documentation – data should be at the heart of what you decide to do and when. What data are you generating against your TPP? What data are you missing? What potential pivots is new data telling you to make?
• Be very careful about over-hiring. The answer to slow R&D should not be to immediately throw more FTEs at the problem. Instead, equip, empower, and focus the people you do have.

Full video

Some topics (with timestamps)

[2:24 - 3:50] Focus >> more FTE generating more data

In biotech, it's easy to think the answer to slow R&D is “just add more people”. Often, this can actually slow you down – while more people might mean more data, the complexity can slow down decision-making while increasing burn.

True productivity comes from understanding how to leverage the people and data you have in the most focused way, not just accumulating FTEs and files. What signal are you looking for? What moves your TPP forward? What gets deprioritized?

In biotech, less is often more, and internalizing this mindset can be a powerful lever. We've also previously written about the related topic of how critical it for leaders to know their own biotech.

[4:30 - 6:37] The Target Product Profile (TPP): building intentionality into the data you're collecting

Know what you're optimizing for. This sounds obvious, but a surprising number of people can't answer this when pushed. That, or they ask the question too late. One of Paul's main suggestions is for leaders to ask this question as early as possible.

As a biotech, you're not just arbitrarily chasing a milestone. You're navigating a series of inflections points so that you can reach market with a drug profile (TPP) that can win. Work backwards and ask yourself:

• What profile will you need to compete in 6–8 years?
• What attributes actually matter?
• What are you tracking now to make sure you get there?

Dimension recently posted on why TPPs and not falling in love with your molecule is so important. It's also the reason we designed Kaleidoscope's compound comparison dashboards – to help teams prioritize compounds that are converging on the profile they’ll actually need to win.

[11:00 - 13:48] Asking tough questions and removing emotions from decision-making

Biotechs love to think that they're data driven, but behind the data are people, and people can make it harder to confront difficult questions. Decisions can end up hinging more on belief than signal. Paul shared a helpful mental model from his time at Novartis: "Real, Win, Worth".

• Is the market real?
• Can we win?
• Is it worth it?

The only thing worse than failing as a biotech along the way to clinic, is for the science to succeed only for the market to not care (competitors offer superior product, doctors won't prescribe, etc.) Asking these simple questions can be surprisingly effective for cutting through noise and prompting making tough calls earlier.

[20:42 - 23:18] Be wary of when emotion is trumping data

It's common for companies to go off of 'gut feel' or trust emotion when making decisions. After all, a company is a collection of humans, and humans are prone to leading with emotion. Sometimes, this can be a good thing, like when a passionate scientist champions a drug

However, biotechs often ignore what data is telling them, and emotions lead to things like sunk cost fallacy that can put the company at risk.It's really important to always pull yourself back to the data, and understand the signal that that data is telling you.

After all, you're ultimately going to have to convince someone to spend $50M or $100M on you, which will come down to whether there is compelling data.

[24:19 - 25:58 ] Kill programs as fast as possible

One of Paul's most common observations is how many companies take weak preclinical programs forward because that’s all they have (or because they assume more shots in clinic = better odds). Anything less than an excellent shot will be a major drain on your resources – time, money, people.

Instead, the goal should be to get to clinic with an excellent program. In the early days, cast a much wider net. Work on a dozen preclinical programs, because you won't know what's going to stick before you start. But then kill as many of them as you can, as quickly as you can. The further along you are, the more you want to focus on the precise programs that look super promising.

That’s how you build a focused funnel and raise your odds in the clinic — even by a few percentage points, which can make all the difference.

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.