Clinical Trials: Event Based Investing & Analysis
By Jason Hines on June 29, 2009
Some events are more obvious than others as being “investable”. One good example is clinical trials for pharmaceutial, biotech, and medical device companies. Outcomes of clinical trials can be part of judging long term value of a company – and have short term significant impact on stock prices – obviously potentially both positive and negative.
The potentials to use information about clinical trials in an investment process could include
- Judging the long term fundamentals of a company’s clinical pipeline based on data, information, and rumors of both a company and its competitors’ drugs. Could be used both to find warnings about existing holding or part of an argument to get into owning an equity.
- Watching operational risk on holdings in portfolio, both directly on holdings and potentially on collaborators/partners of holdings.
- Tactical trading in a company – based on short term information advantages re: trial completion, trial problems, etc. Such information might have been released to a local/international source or slipped out through a niche publication, or as an amalgamation of subtle signals in say twitter or blogs.
- Quantitative strategies where types of clinical information is correlated with e.g. financial instrument volatility.
Recorded Future and Clinical Events
Recorded Future harvests an event type called FDAPhase, which finds clinical trial events in sources ranging from SEC filings to company conference call transcripts to mainstream/niche media to blogs, and captures company involved, product type, product, and stage of trial – see for example here an entry on BioMarin drug/compound PEG-PAL from PR Newswire.
As an example, the above event entry on BioMarin captures that this is a phase I trial on the PEG-PAL compound out of a niche type news source. Interestingly enough, the time point is in the future: July (harvested in early June) – “The company expects to initiate the Phase 2 clinical study in late June or early July, pending institutional review board (IRB) approval from the clinical trial sites.”
Investors will likely be particularly interested in these sort of upcoming/future clinical events – even if the specific event above is not the most interesting event from an investment point of view, it is a good pedagogical example.
Exploring Near Term Pipeline
To find near term clinical events we can do the query FDAPhase Next month or and to find near term clinical events for a specific company, say Human Genome Sciences, do the query FDAPhase Human Genome Science Next month
and you will find a series of clinical trials events with time points in July as well as events ranging across the year – including July.
At the top of the list we find regarding the Human Genome Sciences drug BENLYSTA “Two Phase 3 trials of BENLYSTA are ongoing, with results expected in July and November 2009.” We might want to dive deeper into the July and November time points – can we find out more about expected outcome, are there potentials for upside, or does these events really just pose risk to us with little upside?
You may wonder, which of these events are actually investable? Obviously some of them are “matter of fact” and the information is out in the market (like probably the above BioMarin news – but on the other hand it might be out in the news but still not discounted into equity prices if it’s a not very well covered small/medium cap equity or that the commentary regarding the upcoming event is interesting (perhaps a niche or blog publication providing color in an interesting way allowing you to put 2 and 2 together in a unique way) OR that news simply has leaked out in one way or other – for example through social media such as blogs or twitter – re: perhaps a local experiment site has had problems that gets reported in local/overseas media.
Long Term Pipeline
We can also look further into the future by just posing the query FDAPhase Future, where we literally find 100s of results – with presumably many interesting areas to dive into.
Now, instead on finding single events we may also use this to rapidly collect information rich articles on companies or disease areas. For example the query FDAPhase Johnson & Johnson Future
yields “J&J outlined upbeat plans to file for approval of three new drugs by the end of 2010 and up to eight more by the end of 2013.” If you’re researching J&J this might be a great starting point for further discovery.
A great information source is earnings call transcripts – for drug companies they are gold mines but there are many to get through. Out of Cephalon’s Q1 earnings call transcript nicely provided by SeekingAlpha we find “If the results are positive, NUVIGIL could have an indication to treat excessive sleepiness associated with TBI towards the end of 2012.” Potential for finding upside in Cephalon? We find this rapidly by running the search FDAPhase Cephalon
Using Recorded Future’s integration with Google Finance we can also easily overlay clinical events on for example pricing data – in this case to explore out clinical trials data have affected Pfizer stock price.
Obviously pretty much all of the above should be quite interesting to someone in a pharmaceutical company investor relations office, market research groups, product/therapeutic area managers, etc. Regulators and market surveillance group should also be interesting users.
Combining this type of analysis of clinical trials data with product release events and and product problem/recall events would also be highly interesting.
Finally – assuming that we have a large repository of historical clinical trials event (we do!) it would be very possible to go back in time and develop a model that takes into consideration historical pricing, volume, and volatility data across say small, medium, and large cap pharmaceutical, biotech, and medical device companies – and correlates this with clinical trials event types by stage I, II, and III and type of drug/therapeutic area. This could potentially yield a very interesting model allowing us to predict pricing volatility given therapeutic area, company size, biotech vs. medical device, etc. We will return to this subject in a future blog entry.
As always, we welcome your comments below!