Although many Americans make regular use of pharmaceuticals, they don’t usually pay too much attention to where those drugs come from. For decades, big pharma played a walk-on role in the occasional newscast or Congressional hearing, mostly focused on costs or the risks of addiction.
That all changed with the appearance of COVID-19. For nearly a year, almost everyone was glued to news reports about the race to find a vaccine. mRNA and spike proteins became part of the daily conversation. And when those vaccines were released, saving millions of lives, the importance of pharmaceutical research and development really hit home.
The race for COVID-19 vaccines really drove home the importance of fast pharmaceutical development for billions of people.
The groundwork behind those vaccines was laid over decades, though. Advances in technology were waiting in the wings for just such an emergency. When the U.S. government cut a $31 billion check, the industry kicked out a solution.
Now, a new kind of technology is offering yet another big boost in drug development. Artificial intelligence is about to kick off a new wave of treatments and therapies… and has the potential to make them affordable for everyone.
The Pharmaceutical Industry is a Powerhouse within the Massive American Healthcare System
While the COVID vaccines got all the limelight, drug therapies have been important in American healthcare for quite a while.
The National Center for Health Statistics reported that, as of 2018, almost half of the population in the U.S. used at least one prescription drug. Doctors proscribed more than 1 billion drugs, and almost three quarters of all medical visits involve a prescription.
Those numbers are going to keep climbing. A 2022 study found that overall pharmaceutical expenditures in the U.S. grew by 7 percent compared to 2020, with usage up by almost 5 percent.
With staffing shortages and hospital stay costs increasing, drug treatments are going to continue to be attractive for medical professionals in every field.
That’s going to put a lot of pressure on pharmaceutical R&D. With a shortage of pharmacists impacting the field just like other healthcare jobs, it hasn’t been clear how the industry can keep up.
Then artificial intelligence came along.
How Artificial Intelligence Will Change the Face of Pharmaceutical Research
Pharmaceutical research has been one of the early wins for applied artificial intelligence. In 2023, AlphaFold, a product of Google subsidiary DeepMind, used highly trained neural networks to predict protein structures for nearly every known protein. As the essential building block for new drugs, it was a game-changer. Former experimental methods could take months to find even a single valid structure.
AlphaFold won the 2023 Lasker Award for Basic Medical Research for predictions of protein structures.
But that’s just one potential use of AI in pharma R&D. The kind of large-scale molecular interaction and reactions that deliver drug effects are well-aligned with machine learning computational models. This can allow AI to simulate and predict effects from compounds without the time, risk, and expense of conventional development. That can give a huge boost to:
- Drug design for specific diseases
- Targeted and designer drug development modeling
- Manufacturing and chemical synthesis techniques that optimize drug creation
- Reviews of existing compounds for secondary effects
- Reducing risk of unwanted side effects through extensive modeling
The power of these AI models means that designers are playing with fire, however.
While the bright spot for pharma development can mean curing cancer, reversing aging effects, or other amazing benefits, the dark side is in the potential for devastating new toxins, enormously addictive substances, and unpredictable side effects. AI researchers in pharmaceuticals will have to tread lightly and move carefully to ensure their work isn’t abused.
What Kind of Jobs Are Likely to Emerge in AI Pharmaceutical Development?
Most of the jobs for AI professionals in the pharmaceutical industry today fall squarely in the realm of theory and experimentation. AI research scientists work hand in hand with pharmaceutical researchers to develop models and test them to ensure the results are safe and acceptable.
That means a lot of machine learning model development and engineering, and training roles. Assembling data and working closely with other scientists to ensure that models are being trained accurately and consistently will be most of the early work in pharma AI.
In time, however, more and more positions are likely to fall into AI engineering and programming. AI for automatically assessing potentially lethal drug interactions will need to be integrated to pharmacy information systems. Decision support models will have to be integrated with other clinical systems.
For the most part, these positions will be at major pharmaceutical manufacturers and vendors. University health systems, particularly those heavily engaged in research, will also offer a home to AI pros in this field.
There will also likely be government jobs for AI scientists as more and more AI-tailored compounds are created. The pharmaceutical industry is heavily regulated, and federal agencies will play a role in ensuring that their creations are safe.
AI Pharmaceutical Development Requires High Levels of Specialized College Education
Getting into those jobs is going to mean a master’s degree at a minimum, and most likely a PhD. While the field is exploring the cutting edge, it’s going to take creativity and in-depth education in AI and machine learning from advanced degrees to create the breakthroughs.
There are already many programs available that offer the specific kind of coursework that is useful in pharma AI. A Master of Science in Artificial Intelligence in Biomedical Engineering or a Master of Science in Intelligent Systems Engineering Bioengineering track sets you up with the right mix of chemical, biological, and machine learning for these careers.
There is even a Master of Science in Artificial Intelligence and Computational Drug Discovery and Development that combines the typical machine learning and coding courses with specialist studies in pharmacokinetic and pharmacogenomics to foster skills specific to development research. Other exotic options can include a Master of Molecular Science and Software Engineering.
For the folks who are most serious about delivering cutting-edge innovation in pharmaceutical AI, there are also dual degree programs on offer. Combining a PharmD (Doctor of Pharmacy) and an MSAI makes you a dual threat: an expert who understands the chemical, clinical, and computational angles all at the same time.
For professionals who have already earned a degree in AI or computer science but want to upgrade their skillset to work in pharmaceutical R&D, certificate programs offer an option short of a full second degree. Taking less than a year to complete, and costing far less to earn, an option like a Data Science and Machine Learning for Biotechnology Certificate Program can build on your existing skills with pharma-related knowledge.
There are also options that are less focused on AI, but which can boost your pharma development knowledge, like a Drug Product Development Certificate. Offering overview courses that introduce you to regulatory principles, the drug development process, and basics of chemical and molecular interaction, these can be a valuable addition to core AI skills.
Professional Certifications Help Signal Skills in AI and Pharma Development
Professional certification is a different beast than educational certificate programs. While you acquire knowledge and skill from a college certificate, just as you do from degree coursework, a professional certification is about testing and validating those skills for employers.
Both technology and medicine are fields where professional certifications are the norm, so you should expect to stack a few of them on your resume if this is your path. For technical skills in AI and machine learning, you can find all kinds of certification options from both industry groups and vendors.
There aren’t specific certifications for AI in pharmaceutical R&D, however. But there are specific certs that are aligned with the field, like the PDCP (Pharmaceutical Development Certified Professional™) from the Center for Professional Innovation and Education. These offer some of the technical pharmaceutical development training that most AI professionals will have missed. At the same time, it assures potential employers that you’ve mastered additional skills in areas like cell and gene therapy, CRISPR, and principles of chemistry for pharmaceutical science.
If you’re looking for an area where you can start applying AI and making a difference to the world right now, pharmaceutical R&D fits the bill.