We are in what seems to be the ‘golden age of biotech.’ New companies are being created every year, and new astounding discoveries are being made, improving the lives of many (fig. 1). Not only this, but more and more data scientists are becoming paramount for these types of companies.
The biotech sector presents tremendous opportunities for investors, but it also presents grea opportunities for data scientists who want to use their skills to develop treatments and therapies. Understanding what to look at in biotech companies will help you choose the best investment or work opportunity. This is why here we will analyze some of the hottest biotech stocks and what they would mean for the data scientists working for them.
Before we name some of the most up-and-coming biotech companies, we need to understand what makes a company promising in the space. There are a few keys to look at: pipeline, area of focus, corporate philosophy, capital structure, and its financial options.
In biotech and pharma, the pipeline is considered to be the most important factor. How many products are you developing, and in what phase are they? It is an excellent indicator of the future of the company. Especially when it comes to medical advances where the rate of failure is approximately 90%, having a robust pipeline will increase the chances for at least one product working out and making it to the public.
The company’s focus area is also a good indicator of future financial performance. In the medical sector, not all diseases are of equal value. Investing a lot of time and money but coming up with the cure or treatment for cancer, Alzheimer’s, COVID, and other high-value diseases is more worth it than a breakthrough medicine for the common cold, for example.
Additionally, assessing the company’s plans for it’s existing products is also crucial for understanding how profitable it might be. It is one thing to develop new products and market them, but licensing products to bigger producers and generating royalties can be very profitable, as well.
Finally, understanding a company’s capital position is important to assess their stability. Developing new treatments – the scientists and researchers, the trials and tests – is not cheap so biotech companies burn a lot of money in the first few years of their R&D cycles.
The good news is that the biotech industry keeps on growing and amassing billions of dollars in investments. As Melanie Senior, describes it in her article for Nature:
“The biopharmaceutical industry largely has been spared from the public market rout that has gutted most economic sectors since COVID-19 hit. After an initial, indiscriminate shock to stock prices in March 2020, investment in biotech companies listed on the stock exchanges has actually increased. The Nasdaq Biotechnology Index emerged from the slump to reach a five-year high — up 11% since the start of the year, following a 20% rise in 2019. Biotech initial public offering (IPOs) have also picked up; in June, the over two dozen 2020 listings had together raised nearly $8 billion — more than over the same period in 2019.”
This is great news not only due to the incredible breakthroughs and discoveries that can be made but by the many opportunities that this brings for the people working in these companies and sectors, like data scientists.
So, which are the hottest biotech companies that might be worth looking at if you are a data scientist?
Let’s start with the ones that are already public:
Founded in 2012 and public since June of 2016, Axsome develops novel therapies to manage central nervous system disorders. They currently have three drugs on phase 3 and one on phase 2. Its most crucial lead candidate drug at the moment is its AXS-05 drug, which targets depression and Alzheimer’s disease-related agitation, and also seems to have the potential as a smoking cessation drug. In April 2021, its FDA application was accepted for Major Depressive Disorder. The FDA gave it priority review – meaning it will take action on the application within six months.
If approved, its depression treatment drug, and other candidates, could mean a market opportunity worth over $9 billion globally. According to nasdaq.com: “Investors are quite bullish on the candidate, because its phase 3 efficacy and safety data were so positive.”
A development-stage biotech company that focuses on developing novel small molecule therapeutics for the treatment of cancers.
Exelixis currently has four drugs already on the market and several in the early stages of development. By far, its biggest winner is CABOMETYX®, a drug for renal cell carcinoma and hepatocellular carcinoma, which are the most common types of kidney and liver cancer. It is approved in 54 countries, and the net revenues generated exceeded the $1B for the first time in 2020.
The company went public in 2000 and it’s a member of the S&P MidCap 400 index, which measures the performance of profitable mid-sized companies. Additionally, in November 2020, the company was ranked 17th overall and the third-highest biopharmaceutical company on Fortune’s 100 Fastest-Growing Companies list.
Founded in 1987, Novavax specializes in “Creating Tomorrow’s Vaccines Today.” Their COVID-19 vaccine has not been able to file for emergency approval from the FDA, but the company has stated that it is expected to file for the approval in the third quarter of 2021. Despite these delays, the US government has signed a $1.6 billion agreement to help fund the late-stage development and manufacture of the vaccine.
Additionally, the company is working on a flu vaccine called NanoFlu; if successful, it could generate annual sales of around $1.7 billion.
Founded in 1988, Regeneron initially focused on neurotrophic factors. Over time they have broadened their research and they now develop drugs for autoimmune diseases, cancers, eyes, and infectious diseases. It started to trade publicly on the NASDAQ in 1991 at $22/share. It currently sells for around $500, due to impressive and consistent success.
The company currently has eight projects on phase 3, 13 on phase 2, and 16 on phase 1 of development. They range from hematology to immunology, cardiovascular disease, infectious diseases, and even rare diseases. It collaborates with companies such as Sanofi, Bayer, Intellia, Alnylam, and Teva & Mitsubishi Tanabe.
Since 2004 Vertex was focused on viral infections, inflammatory and autoimmune diseases, and cancer. More recently they have shifted their attention to rare diseases such as cystic fibrosis, sickle cell disease, beta-thalassemia, Duchenne muscular dystrophy, and others.
In 2020 the company was named to the Fast Company’s annual list of the World’s 50 Most Innovative Companies and was recognized as one of the 50 most community-minded companies in the US with the Civic 50 badge of honor.
They went public in 1991 at $9/share and is currently at $213, with a 1-year aim of $279. According to Glassdoor and Indeed, the annual salary average for a Data Scientist at Vertex is between $118,414 and $136,189, which is 13% above the national average.
Founded in 1998, Illumina specializes in the design and development of technologies and assays for analysis of genetic variation and function. This is essential to the booming area known as “personalized medicine.”
They went public in 2000 at $16/share and is currently at $399. Illumina boasts an average salary for Data Scientists of $140,000 per year and they hire data scientists constantly.
There are also some companies with promising futures that are about to go public in 2021 and represent a massive opportunity for Data Scientists:
Day One Biopharmaceuticals
A biotech company that focuses on studying and understanding the differences between children’s and adult’s cancers in order to develop better treatment options for all ages. In the last 25 years, there have only been 12 medicines approved to treat childhood cancers due to “misperceptions about safety, regulatory hurdlers and complexity of impending pediatric clinical trials, and market sizes,” Day One Pharmaceuticals is on a mission to change those misperceptions.
Founded in 2018, it aims to raise more than $100 million with its IPO to fund its clinical trials and expand its pipeline. They are currently looking for a Head of Biometrics.
As they describe themselves on their website: “we represent a new kind of pharmaceutical company with a deconstructed R&D environment that prioritizes data-driven decision making led by subject matter experts. Centessa companies are advancing a portfolio of high conviction programs with strong biological validation,” proving the importance they give to data science.
Centessa focuses on developing medicines in oncology, neuroscience, immunology, pulmonology, hematology, and nephrology. They currently have one drug on phase 3, two on phase 2, one on phase 1 and twelve other candidates in the early stages of development.
They intend to raise $285 million from their US IPO in 2021.
Founded in 2016, they “ are a life science technology company that is leveraging novel next-generation sequencing (NGS) and multiomics technologies to build products that empower researchers and clinicians.” They do this by developing unique and proprietary NGS technology.
Set to raise up to $187 million with their IPO in May 2021. As genomics are a big and important area for Data Scientist, keeping this company in the loop would be a smart decision.
Data Science in Biotech
What exactly does a data scientist does in biotech?
The world of biotechnology is quickly becoming dominated by data. Because of this, the industry is demanding more and more data scientists, analysts, engineers, statisticians and technologists to join their ranks. In fact, there is an annual growth rate of around 28% in job opportunities for data scientists, data developers, and data engineers across the globe for the space.
According to Linkedin’s workforce report, in 2015 there was a national surplus of people with data science skills, but by 2018 the job scene has changed, and now there is a shortage of data scientists (fig. 2). In the report, there was a national shortage of 151,717 people with data science skills in the US. The deficit is seen not only in the tech and finance industries, as was expected, but in almost all industries, these skills of knowing how to analyze, collect, report, and store data are needed.
The US Bureau of Labor Statistics sees strong growth in the data science field and estimates that the number of jobs will increase by about 28% through 2026. That equates to roughly 11.5 million new jobs in the field over the next 5-years.
The exact job requirements, skills, and areas for a data scientist in biotech are varied. Data scientists can go into genomics, drug discovery, safety and recycling, biostatistics, crowd-source R&D, designing and analyzing predictive models, helping make clinical trials more effective, and last but not least, a data scientist skills are also helpful on the more business side like business development and marketing (fig. 3).
When it comes to the skills that are required from a data scientist, they are focused on statistical analysis, mathematics, programming, and some machine learning. In some cases strong communications skills are required in order to present their research to the other members of the company.
On the technical side data scientists need to be skilled in open source programming (Python and R), Hadoop or cloud-based computing platforms (AWS, Google Cloud, Azure, etc.) and SQL. Quantitative skills such as statistical analysis, machine learning & AI-type modeling techniques are often required. In some cases data visualization skills can be very helpful, as well. Some roles in biotech benefit from a background in science (biology, chemistry, etc.), but the vast majority or roles have this as a “nice-to-have” instead of a requirement.
Combining Data Science with the world of biotechnology is a great way to make money, but it is also a great way to use quantitative and technical skills to make a positive impact on people’s lives and society. After years of working in finance or advertising, a lot of people look at the biotech space as a way to use their skills in a more mission-driven organization.
- Senior, M. The biopharmaceutical anomaly. Nat Biotechnol 38, 798–805 (2020). https://doi.org/10.1038/s41587-020-0593-1