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Pharmacology to Payer: One Quantitative Drug Development Framework to Rule Them All

In JRR Tolkien’s Lord of the Rings, the power of the one ring forged by the evil sorcerer, Sauron, is used to control all of the disaggregated, independent kingdoms of Middle Earth. Similarly, but without the malice, the “pharmacology to the payer” (P2P) quantitative framework can be viewed as a way to unite and connect disaggregated and independent disciplines to address drug development market failures. In this blog post, I’ll discuss how the P2P concept evolved from a multi-sectoral collaboration involving clinical pharmacologists, pharmacometricians, specialist physicians, virologists, epidemiologists, mathematicians, and health economists.

A failure to account for payers

Traditional drug development paradigms engage the key stakeholders in a relay race. With each successive independent stakeholder, a baton change occurs. Traditionally, the finishing line has been drawn before the payer. Thus, regulatory approval equals reimbursement, which equals patient access.

Historically, the payer had reluctantly accepted the baton and signed the check. The payer is now saying, “No, I will not accept a baton. I will not write that check and accept all of the risk. Furthermore, prove to me why I should pay the check and why we shouldn’t split the bill.”

Today, the finishing line in Europe is different. Navigating the payer landscape can take up to two years, if it can be navigated. This results in unacceptable delays to the access to lifesaving medicines for many patients. And payers in the US are surely watching attentively to how the US adapts.

Accelerating patient access?

The stagnation of access to medicines to patients has led to various approaches to accelerate developing new medicines and hence, providing patient access.

Adaptive licensing programs encourage regulators and sponsors to engage earlier and identify opportunities for provisional approval of medicines in focused populations with less data than would be considered for broader approval with the commercial opportunity of the sponsor beginning to receive revenue. This addresses only part of the delayed access to medicines for patients. The payer in this environment is still stranded in the wilderness.

Orphan Drug Act

Likewise, the Orphan Drug Act recognized that many rare diseases were underserved and effectively promoted the patient interests earlier in the drug development process. But, the payer is still left in the wilderness. In fact, some of the more perverse examples of lack of affordability have been propagated by these kinds of incentives. Consider the media fallout when Turing Pharmaceutical priced a tablet of pyrimethamine from $13.50 US to $750, an increase of 5,500 percent. How will countries with low healthcare budgets likely respond to subsidizing high priced medicines for rare diseases for their people?

New world: Patient value driven

An attractive strategy to address market failures is to defeat silo-based thinking and bring all key stakeholders on a journey together with greater transparency through the development lifecycle.

By prioritizing patients’ needs and together sitting opposite the problem, we assume that all stakeholders can identify a win-win:

  • The sponsor gains earlier certainty of a path to market and the business case as well as earlier revenues through provisional pricing
  • The regulator attains earlier alignment with regulatory requirements
  • The payer obtains earlier alignment with reimbursements requirements and opportunities to risk or cost share
  • The patient benefits from earlier access to medicines

But, execution of such a laudable strategy is challenging due to difficulties in communicating cross-purposes. Payers, patients, sponsors, and regulators all have differing priorities and goals. Their competencies are different. Their languages are different. To have these conversations earlier in the development process requires a “decoder.”

This is what the pharmacology to the payer concept can provide.

What is P2P?

P2P is a quantitative framework that bridges across disciplines—from pharmacology, pharmacokinetics/pharmacodynamics (PK/PD), epidemiology to health economics—to support more meaningful dialogue between industry regulators and payers.

Our starting thesis was that if the independent pieces of a quantitative framework could stand the scrutiny of the stakeholder groups, and everyone agreed how to link those independent pieces, then the outputs of a quantitative platform would enable meaningful dialogue much earlier in the development process.

The pharmacometrics and clinical pharmacology community has an unprecedented opportunity to build upon the P2P concept to lead impactful solutions that will help address the ensuing market failures in drug development.

P2P test case: Oseltamivir and pandemic planning

Oseltamivir (Tamiflu) remains a cornerstone of national stockpiles, and pandemic planning is a pillar of healthcare policy in all countries.

Optimized procurement and deployment of antivirals is tough. In fact, Australia’s national stockpile of Tamiflu was opened recently due to a severe influenza season with much higher morbidity and mortality than typical. So, governments wrestle with this issue on a seasonal basis.

Pandemic policymakers and planners are effectively “weather forecasting.”Their procurement and deployment decisions are based on big assumptions. But they never know the features of an emerging virus. Moreover, a virus may change during a pandemic, which may alter optimal selection of an antiviral, its dose, and its deployment strategy.

An added advantage of picking oseltamivir as a P2P test case was its relatively rich preclinical pharmacology, epidemiology and clinical evidence base from which to draw on.

Much of this information was generated by Roche’s collaborative dose prediction program that established the component parts of predicting an optimal dose for an emerging virus. Also, influenza health economic data was available.

So, we felt that oseltamivir and pandemic planning ticked all of the boxes for a viable candidate to build a quantitative framework to demonstrate that pharmacology to the payer was possible.

Better procurement and deployment decisions

We sought to use P2P to support better procurement and deployment decisions involving antivirals against emerging influenza viruses.

To illustrate the point, let’s follow some patient journeys: A new influenza virus emerges, and it may have differing degrees of infectivity and virulence. The virus then comes into contact with a patient. This video depicts a multiscale epidemiological model where we’ve seeded an infection. In this model town, the residents move between their homes to their workplaces, schools, or day cares. After infection, the patients change from green to red. As they go to school or work environments, they come into contact with others and propagate the virus.

In the two lower right panels of the video are two scenarios of different treatment interventions of two different doses of oseltamivir in that environment.

During the outbreak, some patients will stay at home, including caregivers, some may be hospitalized, and some may die or return home. At each opportunity, patients come into contact with others. The virus may be more or less affected by a treatment intervention through drug resistance.

With multiple potential scenarios based on infectivity, virulence, and resistance, how can a decision-maker chose which antiviral to use, what dose to give, how much to buy, whom to treat with how much, and the associated cost benefit? How can a decision-maker weigh other interventions like closing schools? Or wearing masks? Or introducing a new investigational antiviral like a monoclonal antibody that only has early clinical data from a human challenge model?

Meaning of  “better” differs among stakeholders

Also, if we need to make better procurement and deployment decisions involving antivirals against emerging influenza viruses, then we also need to recognize that the meaning of “better” differs among the stakeholders. How can we capture and present decision-enabling data to allow transparent communication of different perspectives?

For example, if we were to propose dose regimens of oseltamivir based on deployment or uptake assumptions for viruses of differing infectivity and virulence, a patient would focus on what dose gets her better sooner. A politician may focus on when can we reopen schools and reduce the community’s infection burden. A procurer or a deployer may wonder how this intervention compares to others and whether the spending is better directed to other interventions.

Overarching strategy

We then constructed an overarching map of the component parts of the quantitative framework. Briefly, it included the following components:

  • How to cater to the key inputs of an emerging influenza virus
  • How the virus may cause individual patient symptoms and disease
  • How an emerging virus propagates through a community
  • Where antiviral drugs directly impact an individual’s disease burden or indirectly impact the population disease burden via reducing viral shedding
  • How the population level disease burden impacts healthcare utilization, and ultimately, health economics

This case study has been published in the British Journal of Clinical Pharmacology should you be interested in further information. I also gave a webinar on this topic with my Monash University colleague, Professor Carl Kirkpatrick. I hope that you’ll watch it and let me know what you think in the comments section!


By: Craig Rayner

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