Posted: 31 Mar. 2020 10 min. read

Biopharma business models could look much different by 2040

By Thomas Yang, principal, Deloitte Consulting LLP

In response to the novel coronavirus pandemic, many biopharmaceutical companies around the world have been collaborating with each other, improving data transparency, leveraging accelerated regulatory pathways, and setting up adaptive trials to develop and test new vaccines and therapies. I expect their experience with this global event will likely lead to new practices that will reshape the way business is conducted.

But the biopharma business model had already begun to shift even before we heard about the coronavirus. Twenty years ago, a typical multi-national biopharma company operated a diverse line of businesses. Along with its core products, it might have also produced generic drugs, consumer products, and medical devices. Many of these non-core business lines have since been sold or spun off as biopharma companies have become more specialized. Our latest research explains how we expect the biopharma business model will change further over the next 20 years as the existing model for treating disease evolves.

By 2040, we expect health is likely to revolve around sustaining well-being, curing some diseases, and preventing others from occurring in the first place. In this future of health,  fewer people will have long-term conditions that require ongoing prescriptions to treat their symptoms. We expect the market for some pharmaceutical products could shrink as this vision plays out, which could push the biopharma sector to update existing business models. When I meet with biopharma executives, it’s clear they are thinking about the changes on the horizon, and many of them recognize their business model—and their market—will likely be disrupted.

Force #1: The rise of customized treatments

The business model used by the pharmaceutical industry changed little during the last half of the 20th Century. Manufacturers tended to target chronic illnesses (e.g., high cholesterol, seasonal allergies, and hypertension) that affected large numbers of people. They then developed one-size-fits-all therapies to treat those diseases. But the cost of developing new drugs has become prohibitive, and the number of common chronic illnesses in need of a treatment has decreased. Biopharma has shifted from targeting blockbuster drugs for the masses to focusing on smaller populations of patients with common illnesses. Rather than traditional one-size-fits-all therapies, we expect to see therapies that target subsectors of disease and small cohorts of patients.

Personalized therapies—driven by data-powered insights—could effectively match patients with customized drug cocktails, or design therapies that would work for just a few people—or even a particular person. Rather than picking up a prescription at the pharmacy, personalized therapies—based on a diverse set of a patient’s characteristics including their genomics, metabolome, microbiome, and other clinical information—might be manufactured or compounded just-in-time through additive manufacturing.

Data is at the core of customized medicines. Real world evidence (RWE) could be used to sift through troves of patient data to identify which patients are most likely to respond to a drug (or combination of drugs) and what dose will provide the best therapeutic outcome while minimizing unwanted side-effects. A wealth of RWE from late-lifecycle and generic drugs could be used to inform algorithms that lead to the development of such customized regimens.

Here’s how this might work: Once a drug has been on the market for 10 or 20 years, the original manufacturer might use RWE to identify patient subsets. Evidence might indicate, for example, that one subset of a patient population responds better to a lower active pharmaceutical ingredient (API) dosage, or maybe combinations of existing therapies have better outcomes for certain patients. For progressive biopharma companies, this could be an opportunity to work with clinicians and researchers in the development of new treatment pathways.

The value in this scenario isn’t necessarily derived from the API (especially once a medication loses patent protection), but from the algorithms that inform the specific API and dosing that a patient should receive. Biopharma companies should be at the forefront of understanding heterogenous patient populations. However, being at the forefront will likely require significant investments in data and analytics capabilities. This shift toward increasingly customized treatments could have a significant impact on the biopharma supply chain. Smaller-volume therapies could require new manufacturing capabilities.

Four more forces likely to alter biopharma business models

In late 2019, researchers from the Deloitte Center for Health Solutions interviewed 14 thought leaders (futurists, venture capitalists, digital health leaders, and academics) to find out how they thought the biopharma sector might change between now and 2040. Along with the rise of customized treatments, four other forces emerged that industry observers expect will alter the course of the biopharmaceutical sector:

1. Prevention and early detection: Vaccines and improvements in wellness could help prevent disease, making treatment for some diseases no longer necessary. Advances in early detection will likely enable interventions that halt diseases in the earliest stages—maybe long before symptoms start to surface.

2. Curative therapies: As with prevention, treatments that cure disease could reduce or eliminate the demand for some prescription medicines. Developing, marketing, and pricing these curative treatments could require the biopharma sector to adopt new capabilities.

3. Digital therapeutics: Increasingly effective and scalable non-pharmaceutical (digital) interventions—including those focused on behavior modification—might also reduce or eliminate demand for medications.

4. Precision intervention: Sophisticated medical technology—such as precise medical intervention enabled by robotics, nanotechnology, or tissue engineering—could reduce the need for pharmaceutical intervention. 

Twenty years from now, biopharmaceutical companies might look much different than they do today. We expect their portfolios and capabilities will have shifted to adjust to a different landscape. A drug manufacturer, for example, might acquire a technology company that has developed microsensors that can evaluate how a therapy is being metabolized by the patient. We don’t know exactly how long it will take for these changes to emerge, whether it’s 10, 20, or 30 years. But we are confident that these changes are coming, and they are going to push biopharmaceutical companies to adopt new business models.

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