With up to $1.4B invested in the R&D process per therapy1 and expectations high for a successful launch and revenue stream, the pressure is immense for a new drug to have a successful commercial launch. However, the annual wave of “The Next Big Thing” is strewn with many failed launches. The authors identify three themes and eight interrelated factors which, they argue, if overlooked can negatively impact a launch. In short, prescribers remain Very Important People in a launch, facing challenges around Vulnerability, Incentives, and Personalization.
Scenario: “This new drug—I don’t really understand what they are talking about.”
A generation of prescribers educated 20, 30, or 40 years ago may struggle with the current state-of-the-art medical science supporting the discovery and development of a new treatment. Innumerable examples exist, but hepatitis provides a useful case study. Hepatitis was classified as A, B, or non-A, non-B as recently as the late 1980s. Treatment options for all were limited—a far-removed scenario from today’s subclasses of hepatitis A through E (with other subclasses under study) and multiple treatment combinations. It is thus quite understandable that the science and medicine underpinning a new drug is simply too complicated or too big a leap forward from a physician’s baseline knowledge, potentially triggering a defensive approach toward the adoption of the new treatment or referral to an academic medical center or Center of Excellence. The pharma innovator may want to consider engaging a panel of clinically and “generationally” credible thought leaders to review existing scientific and medical education materials (likely already developed by the pharma company) to determine how best to bridge the scientific and knowledge gap that may have occurred since the prescribing physician left medical school.
Scenario: “I’m just keeping something in reserve.”
A physician’s treatment armamentarium is finite—and deserving, therapeutically challenging cases abound. It is human nature to want to have “something in reserve” for the sickest of the sick. Unfortunately, one consequence is that prescribers may keep a new, efficacious medicine in reserve when the pharma developer wants them to use it. A recent example is the heart failure treatment combination of sacubitril/valsartan, which has faced challenges despite 20-plus innovation-free years in the therapeutic area. The pharma innovator may want to generate evidence on how specific patient populations continue to have unmet needs despite all the existing therapeutic options available.
Scenario: “How does this help my practice?”
The business of medicine is a specialty in its own right and the reduction in the proportion of physicians in private practice is a testament to the challenges of a complex and dynamic reimbursement environment. A novel treatment must therefore be able to communicate how its use will improve the health of individual patients while also supporting practice viability. Given the myriad of healthcare quality and performance measures for which prescribers are held accountable and incentivized to achieve, it is critical to understand how the new medicine will help achieve such measures.
The pharma innovator may wish to consider capturing, at a population-level, the health gain that is “left on the table” due to the underuse of novel medical treatments, i.e., life years lost or similar health events. Such data could then be translated to the individual physician, mitigating the scenario where the value of the innovative drug is lost or, worse, rejected because the prescriber cannot put the potential health benefit into the context of his/her patients and the needs that remain under the current approach to care.
Theme 2: The Challenge of Misaligned Incentives
Scenario: “I get compensated for doing X but this new drug improves Y—how does that help me?!”
Despite all good intentions, it is widely acknowledged that financial and other incentives can consciously and subconsciously drive human behavior. In the context of a pharmaceutical launch, misaligned performance incentives have the potential to meaningfully impact the adoption of a treatment. For example, at the time of the launch of the novel oral anticoagulants (NOAC) class, the National Quality Forum measure focused on the percentage of patients requiring OAC who are on warfarin or Coumadin, and who are under control with an INR between 2-3. The NOAC class does not require INR monitoring. Had this NQF measure not been adapted at the last minute to broaden it to include NOACs, there would have been a perverse incentive to continue to prescribe OAC over NOAC, despite compelling clinical trial evidence of the benefits of the novel therapy in NVAF patients. The pharma innovator ought to examine how practice incentives (financial, quality measure related, or otherwise) may influence prescriber behavior.
Scenario: “If you don’t take the medicine you won’t get the benefit.”2
Consider an older, financially resource-constrained patient on multiple medications. A new drug offers clear benefits over the cheaper generic but the co-pay or co-insurance is not viable, so the provider prescribes a sub-optimal drug that the patient has at least a chance of filling versus taking a “better” drug that is unaffordable. For example, in a diabetic patient, a DPP4, SGLT2, or GLP1 may be preferred to the “standard of care,” metformin. Yet, if the HCP incentive is HbA1c control, e.g., an NCQA HEDIS measure, a financially constrained patient may be more likely to achieve this on the older, generic, and affordable standard of care despite its recognized therapeutic limitations. The pharma innovator needs to recognize that there may be financial disincentives to adopt new health technologies and these may have short- and long-term negative effects on the health of a patient and a population.
Theme 3: Tailor Drug’s Value Proposition to HCPs
Scenario: “Why do I need to change how I treat these patients? I don’t need another new drug for this.”
Increasingly healthcare providers are subject to ongoing assessment of their patterns of care and the health outcomes they deliver. This presents a tension in the adoption of new treatment—balancing the “learning curve” for a new treatment with the reality of being assessed based on data from a heterogeneous clinic population. A physician may, therefore, be hesitant to readily adopt a new drug pending tempered, personal experience augmented with reassurance from his or her peer group—while being sensitive to the monthly, quarterly, and annual metrics by which they are evaluated. The pharma innovator may want to understand the learning curve behaviors for the disease and drug they are launching to help overcome understandable barriers to adoption.
Scenario: “My patients aren’t like the ones studied in the clinical trial; my patients are sicker than everyone else’s so this drug doesn’t really apply to me.”
Prescribers may be unable to translate the clinical trial inclusion/exclusion criteria to the types of patients they see and, rather than seeking these data on their own practice, may adopt a defensive, avoidance tactic. So, despite a physician acknowledging the unmet medical need with a particular condition and a new treatment having a value story that is compelling, it may not be apparent how the clinical trial inclusion/exclusion criteria translate to the risk facing an individual patient or their patient population. The pharma innovator may need to describe for individual and group practices—especially among clinical thought leaders or at marquee healthcare institutions—the types of patients they look after and how these are similar to those in the pivotal RCT, i.e., how “real-world” patients are like those in the trial. Such analyses may need to be widely replicable and made available to inform physician understanding of how to relate the trial patients—their needs and potential benefits gained—to their own patients.
Scenario: “This new drug is for everyone with X? Really?!”
While recognizing symptomatic illness relies at least in part on a patient being able and willing to share, the challenge is exacerbated in asymptomatic illnesses, such as hypercholesterolemia, which are reliant on detection during a planned “wellness” check-up or opportunistic screening visit. Thus, a different challenge facing healthcare providers is finding specific at-risk, sick patients among the population they care for. And if a provider cannot find the patient, they cannot “pull through” healthcare quality improvement initiatives, including appropriate use of a new product.
Pharma should consider developing, publishing, and disseminating a healthcare medical chart or claims-based algorithm (a “signature”) to help practices identify patients likely to have the medical condition that matches the FDA-approved indication for the new product. While such an algorithm is not intended to definitively detect or “diagnose” such patients, it can add value in helping providers and payers identify patients (i.e., raise the “index of suspicion” or diagnostic probability) of who may be at risk. This allows providers to intervene as appropriate. Gibson et al (AJMC, 2011) offer an excellent example in the case of major depressive disorder resistant to multiple lines of therapy.
Innovation is the lifeblood of the R&D-based pharmaceutical industry and continues to bring to the world drugs with the potential to alleviate or cure a great many illnesses. Yet the stakes are high for a successful launch. In an era where physicians are under pressure from all sides and physician prescribing autonomy is increasingly subject to oversight, it is critical for pharma innovators to continue to appreciate the critical role that the physician has in ensuring safe and appropriate use of drugs. We have identified three themes containing eight factors we believe are grounded in the day-to-day issues facing physicians as they examine a new drug and ponder, “What’s in it for me?” For each issue we offer simple, straight-forward advice for pharma to consider.
1. DiMasi JA, Grabowski HG, Hansen RW. “Innovation in the Pharmaceutical Industry: New Estimates of R&D Costs.” J Health Econ. 2016;47:20-33.
2. C. Everett Koop, former U.S. Surgeon General.