Understanding the disease actually causing a person to feel ill significantly increases the likelihood of developing safe and effective therapeutics and interventions that slow, arrest, or reverse that person’s health decline. The better we understand a disease, the earlier we can detect it or intervene to pre-empt it.
People often use the words “illness” and “disease” interchangeably to refer to an unhealthy state. Precise definitions of these words are elusive; the medical literature is filled with debates about their exact meanings. Nevertheless, most definitions of illness emphasize the effects of an unhealthy state—how people feel and the findings revealed by examining them when they do. In contrast, definitions of disease tend to include consideration of the underlying cause (or causes) of their unhealthy state. When it comes to drug development, focusing on disease is critical.
Understanding the disease actually causing a person to feel ill significantly increases the likelihood of developing safe and effective therapeutics and interventions that slow, arrest, or reverse that person’s health decline. The better we understand a disease, the earlier we can detect it or intervene to pre-empt it. The more mechanistic the approach, the more deterministic the outcome. The less mechanistic the approach, the more we are just guessing.
We all know intuitively what it means to be ill—we feel bad due to symptoms like pain, fatigue, and shortness of breath; we display objective evidence that something is wrong, with signs like fever, swelling, or high blood pressure.
Disease, in the sense we are using the term, is a specific biological process that disrupts normal biological function in ways that produce illness. Different disease processes can produce the same illness.
Many of the conditions that we think of as common illnesses, such as heart failure, high blood pressure, type II diabetes, Alzheimer’s disease, Parkinson’s disease, NASH, and obesity are primarily or entirely recognized based on particular constellations of symptoms and signs. For example, Alzheimer’s disease is diagnosed based on presence of progressive dementia in the absence of other known causes of dementia, such as stroke. The diagnosis ultimately requires confirmation at autopsy of the presence of nerve loss, amyloid plaques, and neurofibrillary tangles in the brain.The causes of Alzheimer’s disease remain controversial.
Disease, in the sense we are using the term, is a specific biological process that disrupts normal biological function in ways that produce illness. Different disease processes can produce the same illness. For example, different pathogens can cause pneumonia; different genetic mutations can cause hemophilia. As this distinction suggests, people who appear to have the same illness—that is, the same constellation of symptoms and signs—may have different diseases. Common illness, such as those mentioned above, are especially likely to include groups of patients with different underlying diseases.
The reason that understanding disease is important to drug development is simple: a major factor determining the success of clinical trials is including patients whose disease is attributable to the mechanism the therapeutic is designed to address and excluding patients whose disease is not, even though those in the latter group may appear similar to those in the former group.
Drug developers refer to the problem of mixing different groups of patients in clinical trials as “heterogeneity.” Testing therapeutics on heterogeneous groups of patients is a major, and costly, reason that clinical trials fail. For example, decades of efforts and the expenditure of billions of dollars to develop therapeutics to modify the course of Alzheimer’s disease have been disappointing. A major reason for this failure, in retrospect, was inclusion of heterogeneous subjects in clinical trials. Alzheimer’s, despite its name, is an illness, not a disease.
Society has a major stake in increasing the efficiency of therapeutic development. Testing well-conceived therapeutics in appropriately homogeneous groups of patients is the key.
The two categories of disease in which cause is most well-defined are infectious diseases and diseases attributable to a single abnormal gene. Not surprisingly, these categories of disease have historically had among the highest probabilities of clinical trial success. Their mechanistic targets are clear and causally linked to clinically distinct outcomes, making it is easy to identify whom to treat. Identifying and understanding different infectious agents has enabled the success of antibiotic development and vaccine development to treat various infectious diseases (including the unprecedented campaign to develop vaccines to prevent COVID-19). Understanding single genetic mutations that cause inherited genetic disorders makes it possible to create precisely tailored therapeutic interventions. A major reason the biotechnology industry has tended to prioritize monogenic disorders (including cancers caused by so-called “driver mutations”) is because of the favorable probabilities created when a single offending gene causes a disease.
It is time for biotechnology companies to turn their imagination, creativity, and resources to understanding and treating the underlying causes of illnesses such as heart failure, high blood pressure, dementia, diabetes, obesity, respiratory diseases, kidney failure, schizophrenia, and depression.
It is absolutely critical to develop effective ways to prevent or treat diseases attributable to dysfunction of single genes, but such diseases represent less than 10% of overall disease burden, measured by metrics such as prevalence or morbidity and mortality.
It is time for biotechnology companies to tackle the common illnesses that most people suffer from by determining the diseases that cause them. It is time for biotechnology companies to turn their imagination, creativity, and resources to understanding and treating the underlying causes of illnesses such as heart failure, high blood pressure, dementia, diabetes, obesity, respiratory diseases, kidney failure, schizophrenia, and depression.
A year ago, we introduced the concept of the Biological Century, the dawning era in which advances in our ability to interrogate, understand, and modify biology will generate a virtuous cycle of progress that has broad and profound impact on humanity. Increasing availability of data that capture clinical differences among patients with ostensibly similar illnesses, genetic analyses that show how variants of multiple genes (as opposed to an abnormality of a single gene) are associated with illnesses, powerful bioanalytical technologies that capture events from the molecular level to the level of intact organisms, and new techniques to model diseases computationally and in laboratory models now make the dream of systematically developing effective treatments for common illness within reach.
Making this dream reality will be a win for all stakeholders in health care. By identifying the disease mechanisms that groups of patients share, and developing therapeutics designed to target these mechanisms, companies will be able to increase success rates of clinical trials, decrease the costs of developing drugs, and shorten the time to market. They will be able to develop tests that reveal the presence of disease at its earliest stages, or even before it becomes established, creating a solid foundation for disease pre-emption. The insurance companies and governments that pay for healthcare will gain greater confidence that their payments are for interventions that are appropriate and effective for the people for whom they are prescribed. And, most importantly, peoples’ lives will improve.
This is a future we can all live with.
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