FINAL THOUGHTS
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James R. Prudent, PhD, is chief executive officer at Centrose (Madison, WI). He can be reached at prudent@
centrosepharma.com. |
Due to evolution, genetic changes have profoundly affected how drugs behave in different animal models. Mutations can also affect drug behavior. Such facts lead one to wonder how far personalized genetic-based medicine has come during the past decade.
Personalizing medical care has typically meant using a patient’s medical history, family history, past imaging data, laboratory results, and other tests to determine the best route of therapeutic intervention. The Obama administration wants to computerize such medical information, which promises to save billions of dollars in overall healthcare costs each year. But because drugs and tests are becoming more personalized based on a patient’s genetics, genetic information will need to be considered and developed as a part of any healthcare information technology. The Clinical Lab Fee Schedule will also need to be updated.
For example, since the discovery of the gene responsible for cystic fibrosis (CFTR), newborns that are at risk for cystic fibrosis can be genetically diagnosed, and therapeutic interventions can be initiated. A recently discovered drug for cystic fibrosis, PTC124, may be prescribed only if the patient’s genetics are known. PTC124 works by allowing the ribosome to translate through stop codons, and only patients with premature CFTR stop codons will benefit from this drug. Since numerous CFTR mutations express identical phenotypes, multiplexed genetic analysis is the obvious choice to determine PTC124 efficacy.
Yet when we get sick, our genome may not tell the entire genetic story. Other genetic information may also be important, such as a DNA sequence harboring an infectious, drug-resistant organism or somatic mutations leading to tyrosine kinase inhibitor resistance. Because the genetics of a disease are not always germ line centric, any genetic information that may be used to make or prescribe better medicines for individual patients could be included under the umbrella of personalized genetic medicine. Under that umbrella, personalized genetic medicine has clearly made important strides during the past few years.
Promise and Reluctance
Today, genetic information has become a crucial part of the discovery, development, and clinical testing process of new drugs. Whether or not a drug will be effective for patients harboring certain mutations can now be determined much earlier in the development process. Genetic information has the potential to determine what drugs may be ineffective or too toxic, or how they will be metabolized.
Subtle genetic changes can alter a patient’s response to a drug. In cases in which critical mutations are found, clinical trial sponsors may decide to genetically test all trial patients or remove patients who carry such mutations. The industry has even begun to use genetics to examine why certain drugs failed clinical trials and why some patients were adversely affected by drugs that were later pulled from the market. Whether or not these drugs re-enter the market for smaller personalized sets of patients remains to be seen.
What is also becoming a crucial part of personalized genetic medicine are the clinical genetic testing devices themselves. Today’s devices are capable of simultaneously analyzing multiple genetic targets and can identify minor subpopulations (1 in 1000) of drug-resistant viruses, even when the change is only a single base. There is even talk that this year, patients may be able to have their entire genome sequenced for $5000.
Yet as more promising platform technologies and testing devices hit the market, not everyone in the clinic is jumping forward to utilize them. In many cases, the reluctance to exploit such futuristic capabilities can be attributed to a number of factors including the following: lack of physician acceptance, lack of reimbursement and coverage by healthcare insurers, delivery of results that are meaningful and actionable for doctors and patients, the complex nature of the devices, and the cost.
To deal with such complexity and cost, some IVD companies have answered with shorter run times, fewer handling steps, and comprehensive patient-specific analysis packages. In an effort to lower costs, companies offer multiplexing formats in which multiple targets can be analyzed with one test. But even these offerings have not changed the status quo. The follow-up article will discuss how the slow transition to using genetics in standard practice may speed up as the overall cost savings get factored in.
