All patients do not respond to drugs in the same manner. In addition to age, sex, diet, and cultural background, genetics have significant influence on the safety and efficacy of many medications for different individuals. Pharmacogenomics — the study of how genetic polymorphism impacts drug response — has become increasingly important across drug discovery and development, and there is growing recognition of its potential benefits for personalized treatment to achieve better patient outcomes. While several genetic variants are known to be linked to patient responses to certain drugs/ or drug classes, the use of pharmacogenomic testing in clinical practice remains limited. Once hurdles, such as cost, accessibility, lack of standardization, and the need for greater understanding of the interplay of genetic, epigenetic, and other factors in drug response, can be overcome, pharmacogenomics is expected to be applied routinely.
Importance of Genetic Variability for Drug Performance
It is widely recognized that not all patients have the same responses to all drugs. Even for patients with nearly identical disease conditions, a particular drug may be highly beneficial, completely ineffective, or cause harmful side effects in different individuals. For many drugs on the market today, less than 70% of patients experience an optimal response,1 and 10-45% have inappropriate responses.2,3 Many factors influence patient responsiveness; in addition to age, sex, diet, and cultural background, genetics can play a major role.4 Indeed, the effect of genetics on drug responses was initially demonstrated over 75 year ago.5
The variability in patient responses contributes to significant challenges in drug discovery and development, as the traditional approach still assumes that one treatment will be suitable for all patients.6 Nearly 80% of clinical trials fail to due to lack of sufficient efficacy or safety concerns, some of which can be attributed to this variability.7 Access to genetic information has been shown to correlate with more successful clinical development. In 2021, for instance, two-thirds of the drugs approved by the U.S. Food and Drug Administration (FDA) were supported with genetic evidence.
That is because genetic factors can affect drug metabolism, transport, and receptor activity.6 Quantitative evaluation of patient responses is determined using pharmacokinetic (PK) and pharmacodynamic (PD) data, which provide information on the absorption, distribution, metabolism, and excretion (ADME) properties and the drug targets, signaling pathways, and pharmacological responses, respectively.4 Both can be impacted by potentially tens of thousands of different genetic variations among individual patients.
The study of how genetics affects individual drug responses is known as pharmacogenomics (PGx), a field of study whose importance continues to grow. A key driver is the growing interest in personalized medicine, which requires an understanding of the influence of genetic polymorphisms on drug metabolism to allow development of optimal, individualized treatments.8
In one study, 1,094 variants localized within 6 Å of drug-binding pockets were identified by mapping genomic variability in human drug target genes was mapped onto high-resolution crystal structures of drug target complexes.3 These variants were shown to affect the PD of a variety of drugs. Other researchers studying elderly patients taking five or more medications found that on average that had three of 10 genotypes with PGx-guided prescribing guidelines. Variations in the in personalized CYP450 family of enzymes are perhaps the best known to effect drug metabolism, and can result in lower efficacy and/or increased toxicity issues, particularly in patients taking combinations of common medications.10
Many Mechanisms in Play
Genetic variations can cause different patient responses through many different mechanisms. Both non-synonymous DNA variants altering protein function and non-coding variants influencing gene expression have been shown to influence patient-specific drug responses.11 The structure, function, and/or expression level of the target protein can be modified to prevent effective binding, the rate at which the drug substance is metabolized can be increased or decreased due to variations in metabolizing enzymes, and the manner in which the drug substance is transported can be influences by changes in the proteins responsible for this activity.3,5,10
Variations in amino acids in the drug-binding pocket can result in changes to the geometry, folding, and other physicochemical properties of drug targets. Changes in target expression levels can impact ADME properties and thus the required dosing. Slower metabolism results in higher levels of the drug substance in the bloodstream, which may lead to adverse effects. Variations in transporter proteins can impact how quickly or in what way a drug substance reaches the target site.
Identified genetic variants that affect the amino acids present with the drug-binding pocket, for instance, have been shown to impact the efficacy and safety of several different classes of drugs, including angiotensin-converting enzyme (ACE) inhibitors (ACEis), cholinesterase inhibitors, and microtubule polymerization blockers.3 A meta-analysis of gene variants, meanwhile, clearly revealed the link between polymorphic drug-metabolizing enzymes and negative drug responses.1
Many Potential Patient Benefits
Access to information about genetic variants can inform medication selection and dosing regimens for treatments known to be impacted by genetic polymorphism. PGx testing includes genomic sequencing, genotyping (specific genetic variants known to influence drug metabolism), and the use of biomarker panels that include several genetic markers associated with drug response.6 Bioinformatics tools are typically employed to analyze the large amounts of data generated.
Tailoring medicines based on an individual’s genetic makeup can have numerous benefits, including selection of medications with greater efficacy and minimal adverse effects.6,8,10 Healthcare providers can also use genetic variability information to determine the most effective dosing levels and choose optimal combination therapies. In many cases, significant time can be saved by avoiding the typical trial-and-error process involved in traditional approaches to the selection of medications for many common conditions.
Well-Known Examples
The FDA has established a list of over 100 approved drugs for which performance (either efficacy and side effects) is known to be influenced by genetic variability.4 Individual responses to many of these drugs are linked to variations in cytochrome P450 (CYP) genes encoding proteins responsible for metabolizing common drug substances. For instance, slower digestion of ibuprofen can lead to greater risk of stomach bleeding, while modified metabolism of the antibiotic vancomycin can be fatal. Polymorphisms in CYP enzymes, such as CYP2D6, CYP2C9, CYP3A4, CYP2C19, and CYP2D6 are known to influence the metabolism of antidepressants, anticoagulants, opioids, antiplatelet therapies, and tamoxifen, respectively.3,8 Pharmacogenomic testing has improved the safety and efficacy of blood thinners such as warfarin, owing to patient-specific responses resulting in variations in the VKORC1 and CYP2C9 genes.6
Variants of the HLA-B gene encoding proteins important to the immune system can impact responses of patients with HIV to the antiviral drug abacavir, including risk of severe adverse reactions.4 Statins for lowering cholesterol can, in some patients, cause muscle pain and other side effects due to genetic variations in OATP1B1, BCRP, and CYP2C9 genes.13,14 Meanwhile, Alzheimer’s disease patients with certain variations in the CHRNA7 gene encoding the major subunit of the acetylcholine receptor (α7-nAChR) experience poorer clinical responses to cholinesterase inhibitors (ChEI).5
Patients for whom selection of their antidepressant medication was informed by genetic testing data were up to 40% more likely to be symptom-free than those patients taking a standard treatment approach.12 Enough data has been generated in fact, that genetic testing has been added to the Current Care Guidelines for depression.8
Cancer patients with certain variations of the dihydropyrimidine dehydrogenase (DPYD) gene can have different responses to flourourarcil treatment,3 while those with variations in the gene encoding the phase II enzyme UDP-glucuronosyltransferase 1A1 (UGT1A1) can have different responses to irinotecan, with bone marrow suppression a severe unwanted side effect.5,8 Variations in the CYP, GST, and ABC (ATP-binding cassette) genes are known to influence the activity of cyclophosphamide (CTX), a widely used drug for the treatment of tumors and autoimmune diseases.15
Variants of EGFR and KRAS genes have been shown to affect drugs responses for patients with lung and colorectal cancers, while BRCA1/2 mutations can impact the effectiveness of PARP inhibitors prescribed for the treatment of breast and ovarian cancer.16 Variations in the gene encoding thiopurine methyl yransferase (TPMT) can influence patient responses to thiopurine drugs used to treat hematological malignancies and autoimmune disorders.
Many of the above are FDA-licensed pharmacogenomics applications, including warfarin (CYP2C9/VKORC1), cetuximab/panitumumab (KRAS), vemurafenib (BRAF), abacavir (HLA-B*5701), carbamazepin (HLA-B*1502), and thiopurines (TPMT).1
Challenges to Leveraging Pharmacogenomics for Patient Treatment
Despite the growing evidence for use of pharmacogenomic testing within the patient treatment process, its use remains limited.1,4,6,8 There are many challenges to overcome before genomic testing becomes routine practice.
Fundamental issues with cost and availability must be addressed. There is also a clear need for better education of physicians on the value of pharmacogenomic testing and more infrastructure in support of testing and analysis. Standardized approaches to analysis of pharmacogenomic data are needed that take into consideration other external, patient-specific factors. Wider health insurance coverage will also be necessary. Regulatory guidance will be important, as companies performing pharmacogenomic testing are not currently required to follow any guidelines, leading in many cases to different results for the same patients.
Equally important is ongoing investigation of existing and identification of additional biomarkers to increase understanding of genetic variability and its impacts on drug responses for different disease. Of particular importance is development of more evidence confirming direct links between the two, as currently different recommendations exist (such as from FDA and the Personalized Medicine Coalition) regarding not only which genetic variants are associated with different drug responses but what should be done in light of those identified. For instance, it is important when considering genetic evidence in cancer patients to distinguish between somatic and germline cancer genome biomarkers, as the former effect how cancer cells respond to medications, while the latter influence the PK and PD properties of medications. Similarly, more information is needed regarding the influence of epigenetic alterations/processes and small regulatory RNAs on individual responses to medications.
Role for Pharmacogenomics in Drug Discovery and Development
Recognition of the impact of genetic variability on patient responses to drugs has led to increasing consideration of PGx in clinical trial design, particularly in indications for which genetic polymorphism has been clearly linked to drug performance. This trend is reflected in the growing number of approved drugs accompanied by companion diagnostic tools for identifying specific genetic variants.1 Rather than assuming one drug will be suitable for all patients, more development efforts are focused on finding “the right drug for the right patient at the right dose and time.”
A key example is neurogenerative diseases, such as Alzheimer’s and Parkinson’s, for which clinical trial failure rates are extremely high.17 One study of Parkinson’s patients found that approximately 90% of patients had at least one genetic variant that could significantly influence their response to treatment (positively or negatively), leading to incorrect conclusions.
A separate study found that drug candidates for which genetic evidence had been collected (often after the fact) were approximately twice as likely to advance through the clinic to approval, and that candidates for which the mechanism of action (the causal gene encoding the drug target protein) was backed by genetic evidence were 2.6 times more likely to be successful.18 Notably, however, they found that very few known genetic relationships were explored clinically in a proactive manner and concluded that for drugs designed to modify disease conditions (rather than only manage symptoms), genetic data should be considered when selecting patients for clinical trials across all indications.
Using natural language processing to evaluate over 28,000 clinical trials halted before meeting their endpoints, another group found that lack of strong genetic evidence was often correlated with stoppage of trials due to lack of efficacy and/or safety concerns.19 Other researchers identified 40 germline genetic variants leading to discovery of new drug targets and ultimately new approved therapies for 36 rare and four common conditions.20
Overall, therefore, “gaining a grasp of genome-wide techniques like metabolomics, epigenomic profiling, and sequencing” — a multi-omics research approach — is essential to comprehending the molecular architecture of disease genesis and/or therapy response.”1
High Expectations
The evidence gathered to date linking genetic polymorphism with variability in individual drug responses is strong, and steps are being taken across the industry, from drug discovery and development to patient diagnosis and treatment, to leverage PGx testing and the growing genetics knowledge base. Education of both patients and physicians will be important to increase the appropriate use of genetic testing in clinical trials and for individualizing patient treatments.13,20 Use of genetic biomarkers leveraged for drug development in clinical practice could potentially also improve patient outcomes through selection of optimal medications based on individual genetic variability.1
Collaboration between drug developers, pharmacogenomic testing companies, and regulators will also be important to establish standardized approaches that address much of the uncertainty that currently exists. Some progress is being made in this area, with for example the FDA, Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG) bringing experts together to develop guidelines for clinicians, who, due to lack of any regulatory requirements, are largely responsible for determining if pharmacogenomic testing should be performed.4
Advances in other technologies, such as liquid biopsies (use of circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) for non-invasive pharmacogenomic testing) and gene_editing tools, areanticipated to facilitate the use of pharmacogenomic testing.16 Expansion of testing beyond the well-known gene families (CYP, DPYD, UGT, etc.) and development of more rapid, cost-effective testing techniques should also support more widespread implementation. Development of polygenic computational models to help understand the complex interactions between multiple genes and drugs will also drive further advances,16 as will the use of an “integrated systems approach” leveraging biomolecular-omics data sets and patient history to support both drug development and more effective patient treatment.1
References
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