For an already approved drug, you would use mostly the same model, but you would not need to probability-adjust the cash flows. You would also start modeling revenue in year 1, rather than modeling $0 revenue per year until the year the drug is approved (which is what you'd do for a pre-launch drug). If you look at the google sheet in the video description, basically you'd change the "Clinical phase" in row 39 to "Approved" for every year. Then in row 63 (Probability of clinical success given stage), you'd have each cell be 100%. Then you'd change row 20 (Penetration) so that the sales ramp starts in year 1 (instead of having 0% market penetration for the first few years until approved). You'd also have to change R&D expense in row 38 to only include post-approval R&D costs.

You can model the risk-adjusted cash flows for each program separately. Then you add up the risk-adjusted cash flows from the products. Then you have to account for any general corporate spend that isn't attributable to specific programs, and probability adjust that (I adjust gen corp expenses by the prob that there is at least one program active at the given time, though there are other approaches). You calculate taxes and working capital based on risk adjusted general corp cash flows, and calculate capex and D&A based on either general corporate or program specific risk-adj cash flows.

Using peak sales multiples is a very common and valid valuation method, whether it's the best metric for a given company and whether 5x is the right number depends on the company.

The earlier stage the investor, the less they use DCFs. Most VCs value companies based on comps rather than DCFs. Re where I got my experience: I've worked in biotech finance my whole career, including venture / public equity funds, investment banking, in the biotech groups at big tech companies, and independent consulting.

@@baybridgebio2576 Thanks for the reply! That's an awesome list of proffesional experience. Do you have any advice for breaking into biotech finance and specifically VC? I'm just out of business school with a MSc in healthcare innovation and have started in pharma consulting (mostly on the clin ops and IT side).

Whether you include a balance sheet depends on the use case, but if you are just doing a quick DCF to value a stock for your personal investment you don't need a balance sheet. The only items from the balance sheet that flow directly to the DCF are changes in net working capital. DCFs also require D&A and capex (which occur on the CF statement but flow to the balance sheet). So if you build an income statement and then forecast capex, D&A and change in working capital, you can do a DCF even without a full balance sheet. The rationale for probability adjusting FCF rather than EBIT or net income is that for DCF analysis, we value the business based on unlevered free cash flows. If you use EBIT, you don't capture cash flows from taxes, D&A, capex and changes in working capital. If you use net income, you don't capture cash flows from D&A, capex and changes in working capital.

If I understand the question correctly : you need to multiply cash flows if approved by probability of approval because not all drugs that are submitted for approval are ultimately approved. Even if the Phase 3 studies succeed, and the company submits for approval based on those studies, the drug can still be rejected. So we have to adjust for that.

Link is in the description, let me know if you have trouble accessing it.

You are correct that this is for a single drug. To model a company with multiple drugs, just build a revenue build (like the one in the model) for each major indication of each major drug. You can also model a separate income statement for each drug, and then sum the probability-adjusted cash flows of all drugs, then discount those to get your DCF value. The inputs for each drug come from a variety of sources. You will have to do research outside of the financial statements for most of these inputs. The google sheet example DCF linked in the description has some guidance on where to find these inputs. Most line items have a comment explaining more about the item and where to find the input.

You can just model out the cash flows for each drug, probability adjust them, then add the cash flows together. Then you discount the combined cash flows. Sometimes you can just forecast revenue individually for each drug, then add revenue together, then model the expenses for the combined company. Then discount those cash flows. Depends on the company and purpose of the model

@@baybridgebio2576 got it thank you!

For a clinical stage company, I'd model the value of the clinical-stage assets separately from the platform, and model the assets until patent expiry with no terminal value. Platforms are quite difficult to value, and how you model platform value depends on the specific platform. I generally don't like to value therapeutic platforms with a DCF as a DCF for a platform would rely on so many uncertain assumptions that you can't have much confidence in the DCF output. You can model products using a DCF, but the residual "platform" value is harder to value with a DCF. Most people value platforms using comps but these valuations are still very uncertain and messy. You can check out this 14D9 filing from Synthorx to see how Centerview valued their platform (page 25 on): www.sec.gov/Archives/edgar/data/0001609727/000119312519322708/d855631dsc14d9.htm In reality investors have a hard time valuing platforms and there isn't a ton of science to it. If a platform plays a big part of your thesis just do a lot of technical diligence, understand what products can come from the platform, what differentiates it from competing platforms, how acquirors might value the platform, when the market will start appreciating the platform value, etc. And run sensitivity analyses on the impact of the change in platform value impacts share price.

@@baybridgebio2576 Got it thanks. Do you have any resources that discuss techniques for valuing a platform?

Platforms are generally valued using comps. You can check out that 14D9 filing for Synthorx that I linked in the above comment for an example. The art is picking the right comp set. Mgmt will always try to create a story that makes the platform seem more valuable than other platforms, investors have to do their diligence to determine whether that story is true.

@@baybridgebio2576 Makes sense! Thank you very much, Richard.

I think any relevant technical degree - biology, chemistry, bioinformatics- is a good foundation. Most funds also want to hire people with relevant advanced degrees - PhD or MD. But IMO the most important thing is to be able to talk to experts in different fields, then synthesize and critically analyze what they say. Biotech requires so many diverse and advanced technical skills that no one person can understand everything.

@@baybridgebio2576 Okay, thank you!

Should be fixed now. Thanks for the heads up!

@@baybridgebio2576 Thanks for sharing and quick reply. Really appreciate