As I write this article, the multi-week Contract Pharma 2021 Annual Conference programming is twilighting for another year. I’m delighted to once again have been a part of this year’s great string of industry luminaries, and a very energetically-participatory group of attendees. When we all work together to move the industry forward is when we ALL benefit, including the ‘we all’ part of us which is the patient aspect where healthcare that we help to commercialize can also be used to help our friends and families. When anyone asks, “Where is the industry going next?” our typical answer has something to do with R&D.

R&D is a Surrogate Measure for the Future of Our Industry
Many investors, industry pundits and other soothsayers use R&D’s budget to revenue ratio as a proxy for a company’s willingness to innovate. This is a very crude measure, because of the variation that exists in ‘R&D’ practices, as well as the serendipity of different molecules or therapeutic modalities. But broadly speaking, pharma R&D represents the ‘What’s Next’ in the industry—targets being investigated now, the molecules being trialed and the delivery systems being refined—all represent snapshots of what will be on the market in the next 5 to 7 to 10-plus years. For this reason, we need to listen carefully to what the data from R&D are saying.

Data Are the Opposite of ‘Belief’
One theme I touched upon when I gave the Annual Contract Pharma Conference Keynote this year was the idea that data aren’t belief. When we design and run clinical trials, we do so in order to collect empirical data of a randomized and controlled sort (RCT). These data have greater strength of freedom from bias and association than data collected in other ways, because they are designed to be collected thusly. There exist so many horrendously-authored articles and papers, especially during the COVID-19 era suggesting weak associations of an observational nature (e.g., hydroxychloroquine, ivermectin, etc.). When subjected to the rigor of controlled methods, or meta-analyses, the seemingly-positive effects evaporate and we’re left with the null results of the expected ineffectiveness of the prosaic.

But when we collect our data properly, and in a methodologically-rigorous manner, we can have greater strength in our convictions that the signals we see amid the noise didn’t arise by chance. We all rely on the FDA (and EMA, MHRA, etc.) to adjudicate new drug decisions based on data exactly so that we’re not in the business of peddling snake oil based on subjectivity. Belief requires faith. Data require empiricity.

Science Dies When We’re Not Empirical
But null results are important results! Knowing what doesn’t work can be as important as knowing what does work. What we can’t allow to happen is the ‘File Drawer Effect,’ which is the notion that null results are somehow less important, less valuable, or less newsworthy than positive results. If the ancients conducted a study geared at determining if Ra, the Egyptian Sun god, actually brought the Sun up into the sky every morning, after a long evening of battles, and they came up empty-handed (i.e., no evidence for the presence of ‘Ra’), this would be a null result.

But is this result any less compelling a piece of datum than another type of result? It is a piece of inductive information that strengthens the argument against Ra, and in favor of an alternative hypothesis—perhaps gravity. Likewise, we often discuss and publish more often (much more often, in fact) on those lines of inquiry which have overtly ‘positive’ results, and where a null result just isn’t headline-grabbing enough.

Think of what we all learn, together, when we all share our collective null results: Those software platforms that didn’t work as planned, new documentation approaches that failed at their target outcomes, molecules and molecular pathways that didn’t stack-up as expected. These are all rich data sources that, when crowdsourced, allow us to ALL get to a better future, faster.

We tend to think that those types of (null) results should remain hidden, either out of shame or as IP to not give competitors an advantage. But moving the whole industry forward gives us new avenues and challenges to explore.

Worrying about the competitive advantage of not publishing null results is like worrying that someone is going to leapfrog your failed yoke design for a stagecoach, when the world was inevitably moving to combustion engine automobiles and electric cars anyway. Resisting the urge to be myopic is a great challenge in competitive industries, but doing it well allows for great breakthroughs.

R&D Outsourcing
Big Pharma outsources over 45% of its activities to CROs and CDMOs, and small-to-midsized pharma companies can outsource two-thirds to 100% of their activities in R&D to outsourcing providers, who have a CAGR of >10%.

A fairly recent study (2020) published in the Journal of the American Medical Association (JAMA) which looked at 63 out of 355 new therapeutic drugs between 2009 and 2018 found development costs in the range of $314 million to $2.1 billion per medicinal product brought to successful approval. And in addition, only 12% of the drugs in development were granted approval. So with an average of about $1 billion in new drug development costs, and a 12% success rate through development, R&D Outsourcing helps companies offset huge R&D spend as well as some of the procedural risks inherent in development of new drugs.

According to the U.S. Congressional Budget Office (CBO), Spending on R&D and the introduction of new drugs have both increased in the past two decades.

In 2019, the pharmaceutical industry spent $83 billion dollars on R&D. Adjusted for inflation, that amount is about 10 times what the industry spent per year in the 1980s.

Between 2010 and 2019, the number of new drugs approved for sale increased by 60 percent compared with the previous decade, with a peak of 59 new drugs approved in 2018.

Outsourcing R&D, therefore, provides an avenue for Sponsor companies to be more competitive by improving the efficiency and productivity across the R&D value chain. Also, offloading operational risks to CROs and CDMOs allows for less regulatory pressure directly on the Sponsor company, while at the same time decreasing overall Time-To-Market (TTM) metrics.

Some of the top activities outsourced in this manner include:

• Safety and efficacy tests in animal models
• Target validation
• Assay development
• Genetic engineering
• Human clinical trials
• Late-stage development

As the fashionicity** of different therapeutic targets and molecules (mRNA, RNAi, etc.) continues to shape the industry and approval landscape, R&D outsourcing models will continue to shift accordingly. But what is clear is that the outsourcing itself has been an incredibly successful symbiosis for many, many years, and the trends and financial incentives (with outsourcing industry CAGR >10%) suggest that the vectors for R&D will continue in this direction.

We know that the drugs which gain approval have demonstrated safety and efficacy in the trials, and we know this on the back of controlled clinical trial data. ‘How’ we collect data matters, how we analyze it matters, and putting this into the hands of organizations who call this one of their core competencies has been an industry recipe for success. Don’t leave R&D spend to chance; there are experts out there who can help across all aspects of the R&D lifecycle. 

*The decline of belief in the pantheon of ancient Egyptian deities was occurring between about the 4th and 5th Centuries AD.

**For more on this, see the January 2019 Clinically Speaking column, “Drugs As… Fashion?”

Reference:

• Congressional Budget Office. (April 2021). Research and Development in the Pharmaceutical Industry. https://www.cbo.gov/publication/57126

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Ben Locwin
Ben Locwin, Contributing Editor, Public Health Task Force Member, Healthcare Futurist

Ben Locwin recently keynoted Contract Pharma’s Annual Conference, and discussed some of these topics from a regulatory perspective. He has been innovating and refining clinical trial practices for many years. He has weighed in on ICH GCP modules during development, written trial protocols, and provided strategy for improving human clinical trial outcomes. He has been featured in The Wall Street Journal, USA Today, Forbes, by the CDC, and other top media.