Serendipity: Or How the Drug Development Process Can Reverse Direction

by Tony Pietsch

Alexander Fleming was straightening out his cluttered lab one day in 1928, when he noticed some mold growing in a Petri dish, where he had been culturing staphylococcus. To his surprise, the bacteria surrounding the mold were dead. That chance observation led, famously, to the discovery of penicillin, the first modern antibiotic, and it changed the course of medicine.

In the 1930s, Otto Schaumann, a medical doctor interested in pharmacology, was studying an antispasmodic compound in rats. He observed that the compound caused their tails to assume an S shape consistent with treatment with such narcotic analgesics as morphine, even though the test compound, meperidine, did not appear to be structurally similar to morphine. It did prove to be a narcotic analgesic, however, and in time, its structural commonalities with morphine emerged. Meperidine was less potent than morphine, faster acting and less likely to induce nausea, and today is widely prescribed under a host of trade names, the best-known of which is Demerol.

For centuries, serendipity has played a key role in drug discovery, but when these examples took place, the drug development process was far simpler than it is today. The best-known modern instance, sildenafil, entered clinical trials as a vasodilator to combat angina, but by 1992, it was clear that it was not going to pan out. Pfizer, the company developing the drug, aborted the trial and asked participants to return the unused drug. Many of the men who had been taking the drug, however, not the placebo, balked. Researchers didn't make a connection until rumors surfaced about the drug's sexual side effects, and, more significantly, read a paper on the role of the target enzyme in the chemical pathway of erection. The drug, it turned out, affected the arterial enzymes of the penis far more than those of the heart, and today Viagra™ is a mainstay of men's medicine cabinets the world over.

Serendipity in the Modern Setting
Like Viagra™, nearly half of all drugs on the market today were developed and tested, only to have some other "side effect" become predominant. Because FDA regulations require researchers to retrace their steps when they reposition a drug, the implications for IT professionals are profound. The typical sequence of events that the FDA requires for a drug to reach market is shown in Figure 1.

A serendipitous event can occur at any stage of development, however, dramatically altering the model. Within the preclinical development phase alone, for example, it is not uncommon for many iterations of compound development and testing to take place. Regardless of when serendipity enters the scene, it is likely to cause a quantum change in a drug's or device's purpose, disrupting the traditional linear process. That disruption can cause a divergence of the critical path into multiple investigations, a restart of the program (as for Viagra™ --see Figure 2) or a step-wise reversal of the development process to a point where it can then begin advancing down the critical path again.

How Serendipity Affects IT
IT professionals charged with supporting and documenting drug or device development will find themselves in a quandary if they don't plan for the inevitable twists and turns that happenstance injects into the process—especially because it has been observed that happy accidents like Viagra™ are more the rule than the exception in successful drug discovery or device development.

Because any documentation must account for the data generated during the drug's original course as well as any additional steps based on unanticipated outcome data, as IT professionals, we must work closely with the scientific teams we support and be exceptionally agile, designing into some software tools an unusually high degree of flexibility. We must account for the FDA's requirement that data for review be presented to the agency only in an electronically readable format--itself an evolving set of standards. We must also be able to codify and present the efforts of many different scientific, engineering and medical professionals, even as the required content and structure continue to evolve significantly over the development lifespan of a new product. We must give careful consideration to the necessity of retrieving data collected using hardware and software that typically span several electronic generations. (In the case of Viagra™, it was 13 years before the drug attained formal acceptance for marketing.)

The Changing Role of IT in Life Sciences
Today, the bulk of electronic submissions to the FDA are simply scanned versions of the paper documents that were produced during the long struggle to reach completion, rendered into common readable formats (PDF, Word, Excel, etc.) and placed on transportable storage media. When the FDA and other regulators need additional information, their only route is to consult the project lead or study director, who in response may be forced to reassemble the team, scan through emails and dig into the collective corporate memory, placing an additional burden on the organization and frequently disrupting current work in progress at critical times—a process that adds significant cost.

To ease this burden, scores of entirely new electronic data collection systems are currently under development. The submission documentation they ultimately generate will inevitably contain more hyperlinks to the collected notebook and electronic data, with greater relevancy. Especially challenging as these systems evolve, however, is the need to incorporate emailed meeting agendas, notes and open discussions into the documentation. Currently, these important communications are in large part omitted from the submission, even though they give the data critically needed context. Tools are available to integrate such ancillary but significant sources of information into the comprehensive documentation, but they are first-generation packages for general business purposes (with all of the feature deficiencies typical of early products). And while they are a great improvement over nothing, they do not address many of the concerns specific to the life sciences.

Almost certainly, many of the larger life science players will either customize the existing packages or build their own tools to facilitate the collection and retention of this corporate memory, and with good reason: History has shown that the delays precipitated by FDA requests for more information can be measured in millions of dollars per month for a blockbuster drug and can be a profitability killer for lesser products. At budget time, this cost- effectiveness will likely trump the usual demands for a quick return on investment in IT.

Where Does GIP Fit In?
The compilation of Good Informatics Practices (GIP) promises to fill the gap between the current state of confusion over compliance with electronic submission requirements and future mechanisms for creating Web-like electronic documentation, as well as how to address the explosion of data that genomics, proteomics, diagnostics, metabolomics, (or any other emerging "-omics") are generating. Understanding the role of serendipity in the life science development process will help IT professionals design systems that accommodate a multitude of necessary adaptations, timeframes and technologies, providing the continuity that is essential to the challenging and ever-changing approval process.

Note: The preceding figures have been adapted from the FDA white paper entitled "Challenge and Opportunity on the Critical Path to New Medical Products," found at www.fda.gov/oc/initiatives/criticalpath/whitepaper.html.