The clinical lab and pharmacogenomics – bridging the last mile
Pharmacogenomics analyses the response of individual patients to a medicinal product, to optimize therapy, obtain maximum efficacy and minimize its side effects.
Pharmacogenomics is now increasingly accepted to encompass pharmacogenetics, which focuses only on heritable biomarkers. Unlike the latter, pharmacogenomics also includes the study of proteins and enzymes as biomarkers.
The proponents of pharmacogenomics believe it holds the key to personalized medicine, in which drugs are tailored to a patient’s unique genetic profile.
Roots of pharmacogenomics in Human Genome Project
Pharmacogenomics is among the first clinical applications of the ambitious Human Genome Project, which was completed in 2003. It has already begun making an impact on clinical medicine, and promises much more as new pharmacogenomic biomarkers are identified by increasingly versatile techniques such as single nucleotide polymorphisms (SNP), small nuclear (sn) RNA-mediation and others.
ADRs are research priority
Pharmacogenomic biomarkers are essentially DNA or RNA characteristics that measure normal biologic and pathogenic processes, as well as the pharmacologic response to drug intervention.
The highest priority of pharmacogenomic research is to identify biomarkers for adverse drug reactions (ADRs), which account for one-fifth of all readmissions to hospital and 4% of withdrawal of new medicines.
ADRs are among the leading causes of death, with as many as 100,000 deaths a year in the US.
Pharmacogenomic labelling of drugs
There already are over 120 drugs in the US which include pharmacogenomic biomarkers in their labels. In Europe, the number is smaller, about 35. One reason is that the European Medicines Agency, the pan-EU regulator, has limited authority in the area. This is because of the large number of drugs which have been approved by Member States (rather than the Agency), with updating of the drug label seen as their responsibility. However, “relabelling to include pharmacogenomic data does not seem to be a priority issue” for the regulatory agencies in individual EU Member States.
Pharmacogenomic labelling of drugs, nevertheless, has been standardized in both Europe and the US under three categories: ‘mandatory’ , ‘recommended’ and for ‘informative’ purposes. So far, mandatory pharmacogenomic labelling is required where clinical trials have established the basis for response. In the category of recommended use, there have been no clinical trials (so far).
Typically, biomarker labelling covers the following subjects: drug exposure and clinical response variability, risk of adverse events, genotype-specific dosing, polymorphic drug target and disposition genes.
Considerable attention has been given to biomarkers for a range of widely-used oncology products. Apart from trastuzumab, they include tamoxifen (for breast cancer therapy), irinotecan (metastatic colorectal cancer), panitumumab and cetuximab (colon cancer).
Pharmacogenomic research is also focused on a host of other drugs and drug classes: allopurinol (anti-inflammatories), flucloxacillin and amoxicillin clavulanate (anti-infectives), as well as statins and immunosuppressants.
Companion diagnostics: measuring response to therapy
Biomarkers have made it possible to sell so-called companion diagnostics alongside expensive drugs, so as to direct therapy to the most responsive patients. One of the most prominent examples is the HER-2 test, accompanying Herceptin (trastuzumab), used to fight metastatic gastric cancer. The drug costs €42,000 for a year’s treatment.
Companion diagnostics also enable identification of potential ADRs, for example tests for the HLA-B*5701 allele accompanying the anti-HIV drug abacavir and for HLA-B*1502 with the anti-epileptic carbamazepine. The latter poses a recently confirmed risk of Stevens-Johnson syndrome and toxic epidermal necrolysis (TEN) in Han Chinese and other Asians.
Drug development and relaunch
Pharmacogenomic biomarkers are becoming integrated tools in drug development, to assess pathways encoded by polymorphic genes and to identify the enzymes which lead to the formation of an active drug metabolite, before entering clinical trials.
One new application for pharmacogenomic data is the relaunch of drugs, which have been withdrawn because of adverse events. Novartis, for example, applied in 2009 to the European Medicines Agency to use Lumiracoxib in genetically selected populations. Lumiracoxib is a prostaglandin endoperoxide synthase 2 inhibitor. It was approved to treat osteoarthritis, but was withdrawn in 2005 because of cases of DILI (drug-induced liver injury). Although retrospective genetic analyses revealed that variants of the HLA-DQ allele could predict elevated transferase levels and identify patients susceptible to DILI, Novartis withdrew its application in 2011 due to its inability to provide additional data within the timeframe specified by the Agency.
Generic drugs and pharmacogenomics
Pharmacogenomics is proving to be a weapon against generic drug imports, especially from large, low-cost producers in countries like India.
In its first-ever Recommendation, the European Society of Pharmacogenomics and Theranostics (ESPT) has called for “a harmonized approach to an updatable drug labelling of generic versions for pharmacogenomic information, as is the case for the original drug.” The ESPT cites the case of Plavix (clopidogrel), used for dual antiplatelet therapy and once the world’s second bestselling drug. Pharmacogenomic information on Plavix, it states, “reveals that genetic polymorphisms of CYP enzymes … contribute to variation in the response of individual patients.” It concludes that pharmacogenomic labelling “should be extrapolated to all medications which are marketed as both branded and generic versions.”
Clinical labs have been late entrants
The role of the clinical laboratory in pharmacogenomics broadly encompasses the following components:
- New and expanded pharmacogenetic tests
- Chemopredictive testing
- Disease and risk profiling
In spite of being a frontline player in the application of pharmacogenomics, the position of the clinical lab has been relatively muted and unrecognised.
In 2000, a feature article noted that the “clinical lab has rarely been discussed within the context of pharmacogenomics.” It however argued that, in the future, “clinical labs will be looked to for genetic test development and validation, and for high-throughput genotyping of patients in clinical trials and routine testing.” It urged “both the labs themselves and the industry as a whole” to take cognisance of the fact.
Different from classical genetic testing
Lab techniques for pharmacogenomics differ significantly from classical genetic testing through chromosome analysis. Although state-of-the-art microarrays can interrogate and evaluate vast masses of alleles, the interpretation of test results into clinically meaningful data is complex, sometimes bewilderingly so.
This is because a particular gene mutation does not always result in a predictable phenotypic effect. A host of non-genetic factors can also play an influential role. Included here are the age, gender and ethnicity of a patient; so too are interactions with other drugs he or she is taking, and above all, any impairment in areas such as liver or renal function.
Usable and actionable information on such diverse factors may only emerge after adequate throughput of clinical data and the establishment of correspondences between genotypic and phenotypic markers. The sole entity which can bring such a scale to being is the clinical laboratory.
Meanwhile, physicians too are overloaded by new diagnostic information which emerges by the day, and need guidance from laboratories on how best to interpret and use the information contained in tests.
Unadopted pharmacogenomic tests
One factor that could accelerate the need for more clinical lab involvement may be pharmacogenomic tests which have not been adopted, in spite of evidence that they work. The best examples here are the enzymes VKORC1 and CYP2C9 for the anti-coagulant warfarin, UGT1A1 for the anti-cancer drug Irinotecan. In such cases, there have been concerns that diagnostic test costs may overwhelm the healthcare system, without demonstrable benefit.
At the moment, it is principally academic groups which are addressing such challenges. The price paid here is an acceptance of the fact that pharmacogenomics will only be “adopted slowly as risk-benefit data demonstrate the value of testing.”
Lab tests and healthcare spending
There is a heated debate underway in the US about laboratory testing as a source of healthcare spending growth. In November 2013, researchers at Beth Israel Deaconess Medical Center (BIDMC) announced the results of a review of more than 1.6 million results from 46 of the 50 most common lab tests. They found that nearly one-third of all blood tests were unnecessary.”
Some experts believe that a solution to this problem might be to increase ‘useful’ tests by laboratories, above all those for pharmacogenomic biomarkers. Even if the growth of personalized medicine increases laboratory testing, they argue this will improve a physician’s ability to make highly targeted decisions about patient treatment. This, in turn, may well reduce overall healthcare spending.
Such perspectives were suggested by Ramy Arnaout, Assistant Professor of Pathology at Harvard Medical School, and lead author of the BIDMC study. He argues that “lab tests are inexpensive. Ordering one more test or one less test isn’t going to ‘bend the curve,’ even if we do it across the board. It’s everything that happens next – the downstream visits, the surgeries, the hospital stays – that matters to patients and to the economy and should matter to us.”