By Maxine Bookbinder 

March 5, 2020 | A surge in innovative pharmaceutical drug discovery has coincided with a decline in a return on investment (ROI) in pharmaceutical R&D. But, according to a new research report, a remedy is readily available.  

In the last 10 years, the average return on investment (ROI) in R&D has declined, says Valerie Kellogg, MS/MBA, analyst, and author of BCC Research PHM 218A: ROI in Pharmaceutical R&D: How to Halt the Decline. Viable drugs are becoming harder to find and subsequently more expensive to test and get to market. “The low-hanging fruit is gone. It’s become more difficult to find drug candidates that will make it through clinical trials to market.” 

The most expensive aspect of R&D are clinical trials, which account for 60% of R&D’s costs. Pharma spent $71 billion on R&D in 2017; in the past decade, the average cost to bring a drug to market was $1.8 billion. The high price tag does not guarantee making it to market launch; only about 6.6% of cardiovascular drugs are approved, and 5% of oncology drugs are approved; hematological drugs, at a 26% rate, are one of the most successful.  

The leading approaches to stop the decline, says Kellogg, is to address the cost of clinical trial development, to collaborate with other companies, to supplement traditional research methods with artificial intelligence (AI), and to be willing to change company paradigms. 

In order to remain operational, companies must address the price of clinical development and the best ways to reduce costs and improve ROI. The most obvious way is to stop development of drugs that are not viable. “A company must dig into its clinical development methodologies to try to assess the drug’s chances of making it to market,” says Kellogg. “That’s where AI and machine learning (ML) come in. Predictive analytics can be used at the front end to assess data, contextualize it, and look for patterns and trends. AI can help determine more quickly if a drug will succeed. If data suggests it will fail, it should be stopped. But this is extremely complicated. Companies still struggle with this.”  

Drug development and R&D are rapidly changing landscapes; fewer scientists are standing over microscopes and more IT specialists are sitting at computer terminals. Although big pharma has big bucks, the larger companies, ironically, risk getting run over by smaller, younger ones.  

That is because smaller, newer companies have flexible staff eager to evolve with the changing landscape, says Kellogg. “The older, bigger pharma companies think, ‘We have IT people, we can do this on our own. But they quickly learn they can’t. Companies that try to integrate current systems themselves usually fail; it’s like trying to reinvent a complex wheel. This is very specialized knowledge. They need to partner with companies that specialize in AI and ML.” The companies that survive are the ones that recognize their limitations and subsequently collaborate with small but innovative biotech firms as well as their own competitors with different specialties.  

One such example is a collaboration between British start-up Exscientia and Japanese pharmaceutical firm Sumitomo Dainippon Pharma. They developed a drug for the treatment of obsessive-compulsive disorder (OCD) that, after only one year in development, is entering into a Phase I clinical trial. The drug, DSP-1181, was designed using algorithms that reviewed potential compounds against a database of parameters.  

In a press release, Andrew Hopkins, CEO of Exscientia, said, "We believe that this entry of DSP-1181, created using AI, into clinical studies is a key milestone in drug discovery. This project’s rapid success was through strong alignment of the integrated knowledge and experiences in chemistry and pharmacology on monoamine GPCR drug discovery at Sumitomo Dainippon Pharma with our AI technologies.” 

Some diseases, such as psychosis, depression, diabetes, and heart disease, may lose attention because of added difficulties in their clinical trials. However, rare diseases and certain types of cancers, which can be considered rare diseases, may gain momentum. “The market is smaller, there are fewer patients, companies can charge more for a drug that cures rare disease, insurance companies will pay to certain degree, and it is good PR to discover a drug that cures rare disease,” says Kellogg. “This is an example of the lower-hanging fruit that is particularly challenging to develop to the point of entering clinical trials.” 

Patient-centric approaches in clinical trials are huge cost-savers, says Kellogg, including mobile health and digital technologies as well as AI. Direct-to-patient recruiting particularly stands out since it, in a sense, bypasses HIPPA regulations and goes directly to patients; it has significantly increased successful recruitment for diabetes and some oncology trials. “They can advertise on diabetes websites, blogs, cancer support groups, and specific sites.” 

One example is 23andme, which has collaborated with numerous medical and research facilities and published more than 150 papers to date. With 10,000 kits sold, it has a vast pool of potential clinical trial participants.  

23andme periodically emails relevant clinical trial opportunities to customers who have expressed an interest in participating in clinical trials. They can opt out of being contacted for these purposes at any time. Customer data are shared securely through an authenticated log-in for authorized personnel and only with explicit customer consent. Customers then visit a web page with more details and instructions from the third party running the trial. All trials follow HIPPA applicable rules and regulations.

“We hope to speed recruiting time by engaging 23andMe’s active research participants and surfacing clinical trials that may be relevant to them,” says a 23andMe spokesperson.  

Money in the bank does not guarantee success. A pharma company spending billions on one trial may have a poor prognosis for survival, as well. The bottom line, says Kellogg, is that pharma and biotech can increase R&D ROI if researchers and CEOs are flexible, keep up with tech advances, partner with tech and other specialist companies when necessary, and replace unproductive practices with newer paradigms. “If pharma doesn’t change, it won’t bode well for ROI or drug development.”  

In the next few years, Kellogg predicts pharma will become leaner and create more partnerships with data companies and competitors, “perhaps even playing a greater role in manufacturing and marketing than in development.” 

The report, which Kellogg spent five months researching, includes 79 tables, analyses on ROI in R&D by top pharma companies, analyses of the global market trends for various chronic disease areas, factors used to calculate ROI, discussion of key mergers, acquisitions, and partnerships, and a profile of the top 15 pharmaceutical companies. The full report can be read on BCC Research.