One of the many luxuries of working in an industry for a long time is that you get to witness the many changes that occur. My experience of more than 30 years in the pharmaceutical and healthcare industry, and being around when contract research organizations (CRO) started to become a real force has given me the insights to be able to understand how they came to be, and what transformations have occurred.
The CRO industry has changed from being primarily a small, regional sector filled with former professors and former pharmaceutical employees doing consulting, with one major deal transforming it forever. Quintiles signed a deal worth more than $400 million with Hoechst Marion Roussel to take over its clinical operations team in return for hiring about 500 of Hoechst’s employees and leasing its space in Kansas City. Overnight, it became the first truly global provider and subsequently acquired numerous regional CROs to fill any gaps.
Soon followed the formation of PPDs as a spin-off from GSK’s clinical operations, making the new chief executive an instant millionaire. From there, the industry was really born with more providers and more acquisitions. Pfizer helped to propel this model further by leveraging the functional service provider (FSP) model by outsourcing functional staff, and Groton, Connecticut is now a ghost town in the US, mainly due to this development.
What drove this change from pharma companies running their own clinical operations groups was purely a cost issue, followed by a serendipitous reduction in liability. By outsourcing this service, they immediately turned a fixed expense with large employee-related costs and liabilities into a variable cost, which they could increase or decrease as needed due to varying pipeline needs.
To this day, the CRO business model is predicated on a cost-plus basis to perform tasks based on the estimated human labor cost required to do them.
History is full of economic shifts affecting society, such as the development of CROs, and now artificial intelligence (AI) and machine learning (ML).
Consider Sir Henry Morgan, the 17th century pirate. Yes, the famous rum one! He started as a privateer, working on behalf of the British Crown, pillaging the Spanish fleets and ports, and taking gold at a fraction of the cost of the British navy doing it themselves – reducing the crown’s liability.
In some ways, the pirates were more effective and less costly, but the crown could not manage them effectively. That’s the age-old price of outsourcing.
At his peak, Morgan had 36 ships and more than 2,000 pirates under his command. What happened when the gold shipments stopped, and the British and Spanish signed a peace treaty while Henry was pillaging Panama City? He was declared an outlaw, all pirates were persecuted and hanged, and the powers that be carried on. Henry, however, went on to marry his cousin and gain a knighthood, and he retired as a wealthy plantation owner.
So, here we have the CRO industry, which was built on the needs of pharmaceutical sponsors for a lower cost, and a variable risk-based model that is predicated on redundant labour-based tasks, but sponsors bemoan the loss of control. An economic shift is now occurring in the form of inflation and the introduction of AI/ML.
AI/ML has been proven by global leading technology provider Taimei Technologies to eliminate the human labour resources required and improve the accuracy of doing clinical operations with minimal human supervisory input.
Take the study-build for its electronic data management systems, for example. With all forms completed, edit checks done and coding completed, the database launch was completed in about 15 minutes while using only one study builder, versus the more usual case of six people taking 10 to 12 weeks. AI also does it with more edit checks and better accuracy. That’s just one example of many.
The question is: What will become of labor-based CROs? Should they follow the path of the 17th century privateers, or adapt and adopt this new technology to become more efficient, more accurate and, yes, more controllable by their sponsors?
Based on my training as an economist and commercial leader, who has worked in the CRO industry and led many technologically driven advancements, it’s a question of whether the outsourced model is still relevant in the CRO industry, where many clinical operations roles have been automated and are now being done faster, more accurately and at a lower cost?
Will sponsors take back this role by leveraging new technology as it is amortised, or can it be used on a variable basis as a software-as-a-service (SaaS) model, but licensed and customizable? More importantly, this technology can be adapted to their needs and controlled at a considerably lower cost.
Tied to this decision is this question: What is the tipping point for making this change? I believe the tipping point has arrived. It might not be the large, global pharmaceutical companies leading this change, but the biotech companies.
The reason is simple: Global pharma has invested heavily in this model with its own privateers and boats, and currently owns the seas. Unfortunately, they’re using sail boats, and this new technology predicts not only where they are sailing but also supplies an automated crew who are trained to use a modern-day destroyer.
Effectively, this new AI/ML technology has eliminated the major barriers to entry for biotech companies wanting to develop and launch their drugs faster, safer, and at a lower cost. This change is being embraced by innovative companies as it eliminates many of the issues creating the financial chasm between phase II and phase III.
The first global pharmaceutical company to embrace this change will have a major advantage. But it is a decision that requires the ability to leave your current privateer crew hanging on the docks, like the British did to Morgan’s men, to move forward in the new environment – something that big pharma is not reticent to do, based on past economic shifts, as evidenced in Groton, Connecticut.
The CRO industry has a choice to make: their leaders can retire to a plantation, as Morgan did, or they can adapt and change their model into one that is technology driven and cost-efficient, and become experts on leveraging this technology to deliver clinical trials.
Now is the time to determine whether you want to continue using the old models that made drug development so costly and time-consuming, or embrace the brave new world of AI/ML by first automating labor-intensive tasks that have no bearing on approvals except for enabling faster, more accurate data and safer products.
Start by choosing a technology partner who has already done it, and not an old tech firm that is trying to retrofit a sailing ship with a nuclear-powered engine. This offers a major advancement, delivering the promise of the digital age and, most importantly, it is in alignment with public expectations of the use of AI/ML.