The generalizability of the findings may be limited

The gap

Evidence profile

Stated in the future work and recommendations and cells limitations sections of the source papers, classified as general, drawn from work published between 2021 and 2026, spanning 2 journals. Those papers have been cited 3 times in total.

Supporting evidence — 3 representative gaps

• Personalized Medicine in Anesthesia, Pain and Perioperative Medicine (2021) · cited 3× · doi

  FDA advocates pharmacogenomic approaches in drug development, review, and approval. Multiple drug labeling guidance for industry, recommending the inclusion of pharmacogenomic information in Human Prescription Drug and Biological Product Labeling were published by the FDA. According to a recent study, pharma- cogenomic information in drug labels can be related to indication (patient selection and efficacy), safety (adverse events), dosing (related to pharmacokinetics) or can just provide general information. At present, the FDA provides information on 362 drug-gene pairs. These data are presented throughout many different sections of 88 drug labeling, for instance package insert, depending on prescribing needs, making them challenging for identification (Mehta et al. 2020). Data accumulated over time demonstrate that one of the most common causes of iatrogenic morbidity and healthcare spending annually in the USA are adverse drug reactions. Some estimates state that genetic factors contribute to as far as 10–20% of the total number of reported adverse drug reactions. Pharmacoeconomics data show that adverse drug reactions may cost the US healthcare system up to 30.1 bil- lion dollars annually, due to increased number of hospitalizations, extended hospital stays and additional treatment and pharmacotherapy costs. These facts indicate that proactive pharmacogenomic testing has a potential to positively influence the thera- peutic outcomes, while potentially reducing the cost of healthcare (Primorac et al. 2020). A person who takes a pharmacogenomic test once can have lifetime benefits. A 2016 systematic review investigating the cost–effectiveness of pharmacogenomic screening tests showed that 55% of studies concluded that pharmacogenomic test- ing was cost-effective, 16% of studies showed that it was cost-saving and 13% showed that it was cost-dominant (Berm et al. 2016). Bearing in mind that the perioperative period is the most vulnerable period for the patient and that some patients require postoperative intensive unit care due to their comorbidities and/or complexity of the operation, pharmacogenomics of anes- thetics deserves to be thoroughly studied. In addition to direct drug levels monitor- ing and automatic closed loop control, implementation of proactive pharmacogenomic testing has a potential to aid anesthesiologists to better tailor and guide their patient care with little margin for possible unexpected events. For some drugs, as discussed in the text, clinical guidelines have been developed based on collected evidence. However, the majority of genetic polymorphisms have not been studied in ade- quately powered clinical studies that would show exact correlation of pharmacoge- nomics guided treatment and both positive outcomes and cost-effectiveness. In the future, studies that incorporate pharmacogenomic data and correlate it to treatment outcomes will mark a new chapter in personalized medicine, making new clinical guidelines available.

  generalstated in future workevidence 5/5
  Keywords: drug pharmacogenomic cost information adverse labeling patient healthcare reactions treatment outcomes clinical review related events
• Model-based clinical utility of pharmacogenetic testing and its potential population impact on the use of essential medicines in Zimbabwe (2026) · Frontiers in Pharmacology · doi

  for dose adjustment, alternative medicine selection for indication, or enhanced patient monitoring based on genotype or assigned phenotype (Omran et al., 2026). Some of these testing and clinical action recommendations are also incorporated into regulatory guidance and drug labelling (Kim et al., 2021). Together, these resources represent a significant the supporting available knowledge base pool of implementation of pharmacogenomics in clinical practice. Implementation of PGx-guided treatment has been observed to reduce adverse drug reactions by as much as 30% in a European setting (Van Der Wouden et al., 2020; Swen et al., 2023). It is important to note that this observation is strongly associated with the frequencies for the genotypes/phenotypes of concern in a given population and thus may differ across geographic and ethnic populations even when targeting the same gene-drug pairs for implementation (Nthontho et al., 2022). best-evidence provide studies and the identification of biomarkers, Zimbabwe maintains a national Essential Medicines List (EDLIZ), which guides medicine procurement and prescribing in the public health sector (Organization WH, 2019). In the context of planning pharmacogenomic (PGx) implementation, evaluating the potential clinical and projected population-level impact of pre- emptive PGx testing requires systematic assessment of medicines those with actionable routine use, in pharmacogenomic key implementation metrics such as the NNG, representing the average number of patients who must be tested for a specific genetic variant to prevent one adverse drug reaction (ADR) or achieve an improved therapeutic outcome and the extent of PGx information included in Summary of Product Characteristics (SmPCs) (Tonk et al., 2017). This study aimed to evaluate the potential clinical utility and projected population impact of pharmacogenetic testing in Zimbabwe by focusing on essential medicines pharmacogenomic biomarkers (MAPBs). estimation actionable known with and of

  generalstated in recommendationsevidence 5/5
  Keywords: implementation clinical drug testing population medicines pharmacogenomic medicine adverse biomarkers zimbabwe essential potential projected impact
• Genetic Associations Between Common Medication Use and Osteoporosis-Related Outcomes: A Mendelian Randomization Study (2026) · Archives of Medical Science · doi

  The generalizability of the findings may be limited as all genetic data were from European-ancestry populations. - Medication-use exposures were based on self-report, lacking dosage and duration information. - The study's estimates reflect the effect of genetic predisposition to long-term medication use, not the effect of initiating a specific pharmacologic intervention.

  generalstated in cells limitationsevidence 5/5
  Keywords: generalizability findings limited all genetic data were european-ancestry

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