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Michal Marszal, portfolio manager, focusing on the global health-care sector at CIBC Asset Management.
Within the broader biopharmaceutical space, generally speaking, I look at that space through the lens of both large, diversified pharmaceutical companies as well as the novel emerging biotechnology names.
Within the pharmaceutical industry, this is an industry that is in constant evolution, looking for growth, trying to tap into the latest innovation while trying to most optimally manage their base businesses. What I, generally speaking, look at is the quality of those base businesses, specifically individual assets, their exposure to the most attractive therapeutic categories and geographies, and emerging pipelines that are probably unlikely to be well priced in by the broader market.
An example of a company such as that is a company called Takeda, which is a global biopharmaceutical player. It has a severely discounted base business by the market and a completely underappreciated pipeline of new both late- and early-stage development candidates.
Within the biotechnology segment, the focus is really on best-in-class assets in the most attractive therapeutic categories. And what I look at is for clearly validated science and ideally strong proof-of-concept data, which by the way can be triangulated from multiple sources. And risk management in investing in a segment such as biotechnology is absolutely key, particularly today with the sector having somewhat of a frothy valuation, nevertheless, offering investors a breadth and depth of investment opportunities unparalleled within the global equity space, where there are capabilities of selecting a specific therapeutic category, a given treatment modality and a specific phase of development as proactively at any given point in time.
Here, I would certainly caution a lot of investors as not over-simplifying investment decision-making. Very often the latest and greatest of the technology in the space is of great appeal and gathers a lot of interest without investors, particularly during periods of exuberance, paying attention to existing body of evidence supporting the technologies in focus.
The types of investments we’re looking to deploy capital — good examples of that are companies such as Ascendis, which is working on a very, very high-quality modality for extending the treatment or dosing interval of various different drugs.
Sarepta, which is a company focusing on gene therapy for a variety of mostly muscle disorders with a clear focus on the disorder called Duchenne muscular dystrophy with a plethora of already generated data. And a number of various, very highly focused companies in spaces such as oncology — here names such as SpringWorks, Deciphera or Mersana come to mind, leading assets in development, clearly validated science and a set of very attractive forward-looking, value-creating catalysts.
In the medical technology and life science tools space, which as I mentioned is somewhat less attractive today due to the relative valuations of that sector in the context of global health care, I would still point investors to attractive categories and leadership within those categories, probably the most optimal capital allocation places, companies such as Medtronic or Thermo Fisher, and also the leaders in some of the highest growth segments, such as Illumina, Pacific Biosciences or 10x Genomics, which do offer a really solid long-term outlook for investors.
Within the services segment, the key focus is on the long-term fundamentals. My belief is that scale is key. The best positioned companies in this space in the broader managed-care space in the United States, for example, is a company called CVS, which is currently, an emerging leader with a highly attractive vertically integrated business model that is at the forefront of innovation within the delivery of health care in that specific market.
Other companies of interest, one good example would be IQVIA taking advantage of some of the key long-term trends within the biopharmaceutical research and development, utilizing enormous scale and data analytic capabilities, including various machine learning algorithms, to most optimally design the conduct of clinical trials and increasingly gaining market share in that segment.