After taking a detour to write about some of the legal woes facing the industry, I'd like to return to talk about biotech valuations. In my recent articles Unraveling Biotech Potential and Biotech's Full Monte I went over a few methods for predicting future drug sales. The idea behind those articles was that if we're going to invest in drug companies, then we have to have some idea of how well the products will sell if they make it onto the market.

Sales estimates are only a starting point, though, as a company should not be valued on sales alone. For the most part, large biotech companies such as Amgen (NASDAQ:AMGN) and Genentech (NYSE:DNA) are valued on earnings and expectations for earnings growth. Unfortunately, placing a value on small biotechs such as Abgenix (NASDAQ:ABGX) or OSI Pharmaceuticals (NASDAQ:OSIP) is not nearly as straightforward. To arrive at a value estimate for these unprofitable firms, we have to put in a bit more effort.

Despite the lack of earnings and the fact that valuation methods for small biotechs can be more art than science, I think we can arrive at a reasonable estimate for what these companies are worth. At the very least, we will have a rough idea that is much better than picking a number out of the air.

What's in the pipeline?
After taking a peek at the balance sheet to see how much net cash the company has, the best starting point is to look at a company's product pipeline. Biotech companies are investing shareholder money to hopefully one day have a tangible drug that it can sell for a profit. Therefore, the value of these companies, outside of net cash, is largely based on what these drug programs are worth. What we want to do is derive a net present value for a drug incorporating the costs of its development and the operating profits it will generate if approved.

Before I go into the details, I'd like to mention that there has been a lot of excellent work done that covers the net present value of drug programs. I want to point everyone to the following invaluable resources for additional information:

As is discussed extensively in the articles above, the value of biotech R&D projects can be determined by using a modified discounted cash flow analysis. It is different than a straightforward net present value (NPV) calculation, as it accounts for the likelihood that the drug will fail in clinical trials and not make it to market. Therefore, it is called risk-adjusted NPV (rNPV). This is an adjustment that must be made as experimental drugs have a high failure rate, and it is inappropriate to assume that a drug will work.

Value of a drug
To calculate the rNPV, we have to model potential costs and revenues over the lifetime of the drug and also take into account the probability that the drug will succeed in getting on to the market. I recommend using one of the Excel spreadsheets referenced above to aid in this process as the framework of the models has already been set up.

There are two stages in the drug's life that we need to consider separately to get the rNPV. The first is the clinical trials stage where the company is sinking money into the drug's development. From the current stage of clinical trials until the drug is approved, the project is costing the company a lot of money with no immediate return on the investment. The exception is if the drug is partnered prior to commercialization where the milestone payments provide near-term revenue in exchange for giving up future rights. It can be difficult to estimate the costs of clinical trials, so I recommend using the expenses provided in the spreadsheet from BioGenetic Ventures as a guide.

The second stage is after the drug is approved and starts generating revenue for the company. We can consider this stage as having a duration from the date when the drug gains FDA approval until the year its patent expires. Since generic drugs quickly erode branded drug sales, the vast majority of a drug's value lies in the period between approval and patent expiry.

Costs of going to market
Once the sales have been modeled, the next step is to estimate the drug's operating profit if it is not yet partnered and the company will market it themselves. The operating profit is simply sales minus the costs of manufacturing and selling the drug and also subtracting any royalties or licensing fees that must be paid. It is here that we see the impact of a high cost of goods or the burden a small company faces trying to build out its own sales force. If the drug has been partnered and the company receives a royalty off of net sales, then use the approximate percentage that the company will receive and don't worry about any of the expenses, as the partner will cover those costs.

After all of the annual costs and revenues have been laid out from now until the drug goes off patent, these figures must be risk adjusted based on the likelihood that they will occur. For example, a company that just started phase 2 trials with their drug will have a 100% likelihood of having to pay the cost of those trials. However, they will only have to pay for the phase 3 trials if the drug successfully completes phase 2. If the drug fails in phase 2, the company won't have to incur the costs of running phase 3 trials.

Factoring in failure
Because of the high failure rate in clinical trials, drugs are not guaranteed to ever make it to the market. Therefore, the revenue estimates must be adjusted by the probability that the drug will eventually be approved. The odds of success in the different stages of clinical trials can be roughly approximated using historical data. A good reference on success rates for drugs in clinical trials is this article by Joseph DiMasi. For example, on average, a drug entering phase 2 has approximately a 30% chance of eventual approval, while a drug entering phase 3 has about a 67% chance of eventual approval. If a drug is currently in phase 2 trials, the operating profits must be multiplied by 30% to account for the odds of the drug making it to market. This risk adjustment greatly reduces the NPV and is why the rNPV is a better reflection of a drug's present value than a straight NPV.

The rNPV is the value of future cash flows from a drug after discounting today's money. Choosing a discount rate is arbitrary, but in reviewing articles on this subject I tend to see rates between 10% and 20% used. For this type of project I tend to stick close to 15%.

After modeling expenses and operating profits and then discounting to a present value, it is possible for a drug to have a negative rNPV. Unfortunately, that is a common result, as many drugs do not recover their development costs. As investors we should be able to identify these situations and avoid them like the plague.

The drug companies that I want to invest in are the ones where the aggregate rNPV of their pipeline is positive. If the pipeline does not have a positive rNPV, then the company is just a vehicle for destroying capital. There has to be a return on the investment in the drug programs that warrants the risk of financing R&D. As investors we want to participate in value creation, not in value destruction.

Final thoughts
Calculating the rNPV is just a tool for estimating the value that a drug program brings to a company. However, it can underestimate the drug's value. If a drug launches successfully, it can bring indirect value that is difficult to quantify. For example, the initial formulation can be leveraged to open other doors such as second-generation products, which have value not reflected in the rNPV of the first-generation product.

Building out such complicated models requires making a lot of assumptions. One big assumption is that drug companies will be able to retain the current level of pricing power. That may be an erroneous assumption given the current climate toward prescription drug costs.

In my approach to investing in biotech, the value should be completely obvious. Such as when a company has a few interesting drugs in the pipeline, yet the company is trading close to the cash on the balance sheet. That's a rarity right now, but it was common a year and a half ago. You don't need sophisticated models to swing at those fat pitches. In those cases, the models do have usefulness in pointing out when the company becomes fully valued again, and that can be helpful in setting up a selling strategy.

To learn more about the biotech industry, check out Charly's recent articles:

Fool contributor Charly Travers does not own shares of the companies mentioned in this article. The Motley Fool is Fools writing for Fools.