Precision medicine: Hippocratic meets informatics


Precision versus personal

Precision medicine is in some ways a new medical paradigm. You hear the phrase in reference to many of the latest hot topics in health; the microbiome, bacterial resistance, HIV treatment and cancer. Defining the term is slightly trickier. The US National Research Council’s (NRC) definition is: “The tailoring of medical treatment to the individual characteristics of each patient.” [1] This is fairly interchangeable with the now outdated name, personalized medicine.

Personalized medicine as a term is not popular amongst scientists and clinicians. It was interpreted by many as meaning the design or tailoring of new drugs to the patient; an unsurprising misunderstanding given the above definition. However, this second line of the NRC definition is key … “to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment. Preventative or therapeutic interventions can then be concentrated on those who will benefit, sparing expense and side effects for those who will not.”

Beyond the magic bullet

Hippocrates himself is quoted as saying that: “It is more important to know what sort of person has a disease than to know what sort of disease a person has.” Perhaps patient classification is not such a new idea then, especially if you have ever given blood, but precision medicine is a distinctly modern interpretation. At its heart lies a data process that uses systems biology such as genome sequencing to categorize patients and inform treatment [2]. This is a marked shift in the philosophy of treating disease.

Prior to this shift, the defining framework in medical thinking was the ‘magic bullet’. The first successful hunt for a magic bullet ended in 1909 when Paul Ehrlich and Sahachiro Hata cured a syphilitic rabbit with compound no. 606 [3]. They named the drug Salvarsan and it became the world’s most prescribed, identically for every patient. The race was on to bag more magic bullets and millions of lives were saved as the golden age of antibiotics arrived. The pharmaceutical industry exploded and treatment regimes outside drug centered care became less fashionable.

A new paradigm

Thinking has now begun to shift for a number of reasons. Technology allows us to do things that couldn’t even be conceptualized 100 years ago. Things like sequencing a genome, identifying disease linked genes, curating large data sets and using AI to calculate the most appropriate treatment in highly complex cases. Such data management and consultation was discussed in Infectious Disease Hub’s interview with Mathias Pletz. His team have seen a halving of S. aureus linked mortality thanks to treatment recommendations made after hospital-wide patient consultation. The excitement around such reduction in mortality also nods to the underlying issue, that in many cases the drugs don’t work.

The resistance crisis has forced medical professionals to think differently about how they treat infectious disease. MRSA and C. difficile have ravaged hospital wards and new monsters like Acinetobacter rear their heads. The magic bullets that were the miracle of the 20th century are becoming blunt instruments. The discovery that the huge uptick in hospital C. difficile infections were actually a response antimicrobial treatment demonstrated the need for a different approach to disease [4].

The benefits of precision

Cancer treatment is another area where new approaches to disease are welcome. With no reliable magic bullet, precision medicine is becoming a high priority. Genetic screening for cancer risk is now commonplace and genetic tumor profiling for genes linked to tumor aggression such as HER-2 is increasing [5]. Categorizing people by genotype this way means treatment regimens such as immunotherapy can be applied.

The argument for precision medicine is similar in infectious diseases. Sepsis treatment can be improved by testing gene activity in patient immune systems [6]. Antimicrobials can be chosen by sequencing bacterial infections and identifying resistance genes [7]. Antiretroviral therapy for HIV can be tailored by understanding viral mutations and patient genetics [8].

These precision medicine processes have huge potential and often go hand in hand with precision or targeted drugs. Future expansion of the approach could see microbiome screening in cases of associated disease such as Crohn’s disease become a regular thing. For example, in a Crohn’s patient, metagenomic screening of the microbiome may indicate a large presence of Enterobacteriaceae, a bacterial family associated with the disease [9]. Precision antimicrobials targeting Enterobacteriaceae survival genes could be prescribed, reducing the inflammation, preserving microbiome health and treating a famously difficult condition.

Impeding progress

The issues holding back such treatments are technological and economic. Speed of diagnosis and screening is essential in infectious disease, particularly if you want to avoid a one-size-fits-all approach. Improvements here will likely come from improved bedside sequencing technology, good record keeping, increased use of AI to manage large data and improved understanding of the mechanisms underlying diseases and genetics. These issues can all be addressed but making the process simple and low cost enough for routine use in hospitals is very difficult.

Precision medicine can reduce costs by foregoing expensive unnecessary treatments, but establishing the processes in hospitals can be expensive. As it stands, many companies are developing innovative diagnostics for use in precision medicine but cornering this market may mean inflated prices that prevent widespread adoption of precision practices. If you factor in expensive targeted therapies, the costs can skyrocket. This issue may decrease with time as the precision approach yields results and popularity brings down prices, but widespread adoption will likely be contingent on support from decision makers around the globe [10].

A very modern medicine

Precision medicine therefore appeals to our peculiar age. On a public level it calls to people’s desire for a ‘holistic’ therapeutic approach, promising to reduce unnecessary drug prescription and offer a bespoke, patient centric view of disease. At the same time, it relies upon mass datafication of our personal biology, uses algorithms to make medical decisions and is reliant on complex market forces for its success. However, at its core the approach seems sound and it represents a shift in the way we view disease and biology. Not as an invading army, unchanging and distinct, to be cured by a magic bullet, but as part of our human ecosystem, to be understood and managed. Time will tell if this equates to better treatment.

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  1. National Research Council (US) Committee on a framework for developing a new taxonomy of disease. Toward precision medicine: building a knowledge network for biomedical research and a new taxonomy of disease. National Academies Press (2011).
  2. König IR, Fuchs OF, Hansen G, von Mutius E, Kopp MV. What is precision medicine? Eur. Resp. J. 50, 1700391 (2017).
  3. Strebhardt K, Ullrich A. Paul Ehrlich’s magic bullet concept: 100 years of progress. Nat. Rev. Cancer. 8, 473–480 (2008).
  4. Theriot CM, Young VB. Interactions between the gastrointestinal microbiome and Clostridium difficile. Annu. Rev. Microbiol. 69, 445–461 (2015).
  5. Cancer Research UK. Personalised medicine. (Accessed 13 February 2020).
  6. Lazăr A, Georgescu AM, Vitin A, Azamfirei L. Precision medicine and its role in the treatment of sepsis: A personalised view. J. Crit. Care. Med. 5(3), 90–96 (2019).  /
  7. Quadram Institute. New rapid test can diagnose pneumonia and other lower respiratory infections. (Accessed 13 February 2020).
  8. Cusato J, Allegra S, Nicolò A, Calcagno A, D’Avolio A. Precision medicine for HIV: where are we? Pharmacogenom. 19(2), 145–165 (2018).
  9. Zuo T, NG SC. The Gut microbiota in the pathogenesis and therapeutics of inflammatory bowel disease. Front. Microbiol. 9, 2247 (2018).
  10. Jakka S, Rossback M. An economic perspective on personalized medicine. HUGO J. 7(1), 1 (2013).

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