Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors

Precision medicine, characterized by the personalized integration of a patient's genetic blueprint and clinical history, represents a dynamic paradigm in healthcare evolution. The emerging field of personalized anesthesia is at the intersection of genetics and anesthesiology, where anesthetic care will be tailored to an individual's genetic make-up, comorbidities and patient-specific factors. Genomics and biomarkers can provide more accurate anesthetic protocols, while artificial intelligence can simplify anesthetic procedures and reduce anesthetic risks, and real-time monitoring tools can improve perioperative safety and efficacy. The aim of this paper is to present and summarize the applications of these related fields in anesthesiology by reviewing them, exploring the potential of advanced technologies in the implementation and development of personalized anesthesia, realizing the future integration of new technologies into clinical practice, and promoting multidisciplinary collaboration between anesthesiology and disciplines such as genomics and artificial intelligence.

CYP2D6-guided opioid therapy for adults with cancer pain: A randomized implementation clinical trial

INTRODUCTION

The CYP2D6 enzyme metabolizes opioids commonly prescribed for cancer-related pain, and CYP2D6 polymorphisms may contribute to variability in opioid response. We evaluated the feasibility of implementing CYP2D6-guided opioid prescribing for patients with cancer and reported pilot outcome data.

METHODS

Adult patients from two cancer centers were prospectively enrolled into a hybrid implementation-effectiveness clinical trial and randomized to CYP2D6-genotype-guided opioid selection, with clinical recommendations, or usual care. Implementation metrics, including provider response, medication changes consistent with recommendations, and patient-reported pain and symptom scores at baseline and up to 8 weeks, were assessed.

RESULTS

Most (87/114, 76%) patients approached for the study agreed to participate. Of 85 patients randomized, 71% were prescribed oxycodone at baseline. The median (range) time to receive CYP2D6 test results was 10 (3-37) days; 24% of patients had physicians acknowledge genotype results in a clinic note. Among patients with CYP2D6-genotype-guided recommendations to change therapy (n = 11), 18% had a change congruent with recommendations. Among patients who completed baseline and follow-up questionnaires (n = 48), there was no difference in change in mean composite pain score (-1.01 ± 2.1 vs. -0.41 ± 2.5; p = 0.19) or symptom severity at last follow-up (3.96 ± 2.18 vs. 3.47 ± 1.78; p = 0.63) between the usual care arm (n = 26) and genotype-guided arm (n = 22), respectively.

CONCLUSION

Our study revealed high acceptance of pharmacogenetic testing as part of a clinical trial among patients with cancer pain. However, provider response to genotype-guided recommendations was low, impacting assessment of pain-related outcomes. Addressing barriers to utility of pharmacogenetics results and clinical recommendations will be critical for implementation success.

Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain

There have been few studies on predictive biomarkers that may be useful to select the most suitable opioids to optimize therapeutic efficacy in individual patients with cancer pain. We recently investigated the efficacy of morphine and oxycodone using single nucleotide polymorphisms (SNPs) of the catechol-O-methyltransferase (COMT) rs4680 gene as a biomarker (RELIEF study). To explore additional biomarkers that may enable the selection of an appropriate opioid for individual patients with cancer pain, three SNPs were examined: C-C motif chemokine ligand 11 (CCL11; rs17809012), histamine N-methyltransferase (HNMT; rs1050891) and transient receptor potential V1 (TRPV1; rs222749), which were screened from 74 pain-related SNPs. These SNPs, which were identified as being significantly associated with the analgesic effect of morphine, were then used to genotype the 135 patients in the RELIEF study who had been randomized into a morphine group (n=69) or an oxycodone group (n=66). The present study then assessed whether the SNPs could also be used as selective biomarkers to predict which opioid(s) might be the most suitable to provide pain relief for patients with cancer. Oxycodone tended to provide superior analgesic effects over morphine in patients carrying the genotype AA for the CCL11 rs17809012 SNP (P=0.012 for interaction), suggesting that it could serve as a potential biomarker for personalized analgesic therapy for patients suffering with cancer pain.

Pharmacogenomics of Cancer Pain Treatment Outcomes in Asian Populations: A Review

In advanced cancer, pain is a poor prognostic factor, significantly impacting patients' quality of life. It has been shown that up to 30% of cancer patients in Southeast Asian countries may receive inadequate analgesia from opioid therapy. This significant under-management of cancer pain is largely due to the inter-individual variability in opioid dosage and relative efficacy of available opioids, leading to unpredictable clinical responses to opioid treatment. Single nucleotide polymorphisms (SNPs) cause the variability in opioid treatment outcomes, yet their association in Asian populations remains unclear. Therefore, this review aimed to evaluate the association of SNPs with variability in opioid treatment responses in Asian populations. A literature search was conducted in Medline and Embase databases and included primary studies investigating the association of SNPs in opioid treatment outcomes, namely pharmacokinetics, opioid dose requirements, and pain control among Asian cancer patients. The results show that CYP2D6*10 has the most clinical relevance in tramadol treatment. Other SNPs such as rs7439366 (UGT2B7), rs1641025 (ABAT) and rs1718125 (P2RX7) though significant have limited pharmacogenetic implications due to insufficient evidence. OPRM1 rs1799971, COMT rs4680 and ABCB1 (rs1045642, rs1128503, and rs2032582) need to be further explored in future for relevance in Asian populations.

Use of Drug Claims Data and a Medication Risk Score to Assess the Impact of CYP2D6 Drug Interactions among Opioid Users on Healthcare Costs

Cytochrome P450 2D6 (CYP2D6) activity is highly variable due to several factors, including genetic polymorphisms and drug-drug-gene interactions. Hydrocodone, oxycodone, codeine, and tramadol the most commonly prescribed CYP2D6-activated opioids for pain. However, the co-administration of CYP2D6 interacting drugs can modulate CYP2D6-medicated activation of these opioids, affecting drug analgesia, effectiveness, and safety, and can impact healthcare costs. A retrospective, observational cohort analysis was performed in a large (n = 50,843) adult population. This study used drug claims data to derive medication risk scores and matching propensity scores to estimate the effects of opioid use and drug-drug interactions (DDIs) on medical expenditures. 4088 individuals were identified as opioid users; 95% of those were prescribed CYP2D6-activated opioids. Among those, 15% were identified as being at risk for DDIs. Opioid users had a significant increase in yearly medical expenditure compared to non-opioid users ($2457 vs. $1210). In matched individuals, average healthcare expenditures were higher for opioid users with DDIs compared to those without DDIs ($7841 vs. $5625). The derived medication risk score was higher in CYP2D6 opioid users with interacting drug(s) compared to no DDI (15 vs. 12). Higher costs associated with CYP2D6 opioid use under DDI conditions suggest inadequate CYP2D6 opioid prescribing practices. Efforts to improve chronic opioid use in adults should reduce interacting drug combinations, especially among patients using CYP2D6 activated opioids.

Influencing factors of end-of-dose failure in patients with cancer pain after oral oxycodone sustained-release tablets: a retrospective, case-control study

OBJECTIVE

Comparing the characteristics of end-of-dose failure patients and non-end-of-dose failure patients in the Chinese population and exploring the factors that may affect the occurrence of end-of-dose failure in cancer pain patients.

METHODS

The outpatient with cancer pain from 2016 to 2019 were collected through hospital information system, and patients were included who met the following criteria: patients with the average numerical rating scale  ≥4 points within 3 days after taking the oxycodone sustained-release preparation, titrated to an effective therapeutic dose suitable for patients, had at least two clinical visits information of the patient with a minimum of ≥3 days between visits, the average numerical rating scale of the next visit after the treatment of occasional pain is ≥4, and were divided into end-of-dose failure group and non-end-of-dose failure group.

RESULTS

Age (P < 0.05, odds ratio 0.933), diagnosis of nasopharyngeal carcinoma (P < 0.05, odds ratio 0.009), pain site is the head and neck (P < 0.05, odds ratio 0.005) and the abdomen (P < 0.01, odds ratio 0.021), and the metastatic site is the liver (P < 0.05, odds ratio 0.001) are related to the occurrence of end-of-dose failure.

CONCLUSIONS

Younger patients are more likely to develop end-of-dose failure. Patients diagnosed with nasopharyngeal cancer, with pain in the head and neck and abdomen, and with liver metastases have a lower incidence of end-of-dose failure.

Pharmacogenomics in Pain Management: A Review of Relevant Gene-Drug Associations and Clinical Considerations

OBJECTIVE

To provide an overview of clinical recommendations regarding genomic medicine relating to pain management and opioid use disorder.

DATA SOURCES

A literature review was conducted using the search terms pain management, pharmacogenomics, pharmacogenetics, pharmacokinetics, pharmacodynamics, and opioids on PubMed (inception to February 1, 2021), CINAHL (2016 through February 1, 2021), and EMBASE (inception through February 1, 2021).

STUDY SELECTION AND DATA EXTRACTION

All relevant clinical trials, review articles, package inserts, and guidelines evaluating applicable pharmacogenotypes were considered for inclusion.

DATA SYNTHESIS

More than 300 Food and Drug Administration-approved medications contain pharmacogenomic information in their labeling. Genetic variability may alter the therapeutic effects of commonly prescribed pain medications. Pharmacogenomic-guided therapy continues to gain traction in clinical practice, but a multitude of barriers to widespread pharmacogenomic implementation exist.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

Pain is notoriously difficult to treat given the need to balance safety and efficacy when selecting pharmacotherapy. Pharmacogenomic data can help optimize outcomes for patients with pain. With improved technological advances, more affordable testing, and a better understanding of genomic variants resulting in treatment disparities, pharmacogenomics continues to gain popularity. Unfortunately, despite these and other advancements, pharmacogenomic testing and implementation remain underutilized and misunderstood in clinical care, in part because of a lack of health care professionals trained in assessing and implementing test results.

CONCLUSIONS

A one-size-fits-all approach to pain management is inadequate and outdated. With increasing genomic data and pharmacogenomic understanding, patient-specific genomic testing offers a comprehensive and personalized treatment alternative worthy of additional research and consideration.

Opioids, Polypharmacy, and Drug Interactions: A Technological Paradigm Shift Is Needed to Ameliorate the Ongoing Opioid Epidemic

Polypharmacy is a common phenomenon among adults using opioids, which may influence the frequency, severity, and complexity of drug–drug interactions (DDIs) experienced. Clinicians must be able to easily identify and resolve DDIs since opioid-related DDIs are common and can be life-threatening. Given that clinicians often rely on technological aids—such as clinical decision support systems (CDSS) and drug interaction software—to identify and resolve DDIs in patients with complex drug regimens, this narrative review provides an appraisal of the performance of existing technologies. Opioid-specific CDSS have several system- and content-related limitations that need to be overcome. Specifically, we found that these CDSS often analyze DDIs in a pairwise manner, do not account for relevant pharmacogenomic results, and do not integrate well with electronic health records. In the context of polypharmacy, existing systems may encourage inadvertent serious alert dismissal due to the generation of multiple incoherent alerts. Future technological systems should minimize alert fatigue, limit manual input, allow for simultaneous multidrug interaction assessments, incorporate pharmacogenomic data, conduct iterative risk simulations, and integrate seamlessly with normal workflow.

Role of Opioid-Involved Drug Interactions in Chronic Pain Management

The use of opioids for chronic pain management is extraordinarily common despite substantial evidence of only modest benefits, when compared with nonopioid analgesics. Opioid use is also associated with serious risks, including overdose and death. A growing body of evidence suggests that opioids are involved in significant drug interactions that often go unrecognized in clinical practice. Understanding opioid-involved drug interactions is of great practical importance for all health care professionals caring for patients with chronic pain. In this article, we describe the mechanisms of opioid-involved drug interactions and their potential consequences, which have major public health implications. Additionally, this article provides practical strategies to aid health care professionals in avoiding and mitigating opioid-involved drug interactions in order to obtain a favorable balance in the risk-benefit ratio associated with opioid use. These strategies include using osteopathic principles for chronic pain management, separating the times of administration of the opioid(s) from the nonopioid(s) involved in the interaction, changing the opioid(s) adversely affected by the interaction, changing the nonopioid(s) causing the interaction, and partnering with pharmacists in clinical practice.

Cost avoidance related to a pharmacist-led pharmacogenomics service for the Program of All-inclusive Care for the Elderly

Aim: Estimate cost avoidance of pharmacist recommendations for participants enrolled in the Program of All-inclusive Care for the Elderly. Materials & methods: Convenience sample of 200 pharmacogenomics consultations from the PHARM-GENOME-PACE study. Genetic variants, drug-gene interactions, drug-drug-gene interactions and phenoconversions were interrogated. Cost avoidance was estimated and adjusted for inflation. Results: In total, 165 participants had at least one actionable drug-gene pair totaling 429 drug-gene pairs, of which 158 (36.8%) were clinically actionable. Most (70.5%) pharmacists' recommendations were accepted. Estimated cost avoidance was $233,945 when all recommendations were included but conservatively $162,031 based on acceptance rates. Overall mean cost avoidance per actionable drug-gene pair was $1063 or $1983 per participant. Conclusion: Pharmacist-led pharmacogenomics services added to the traditional medication review can avoid substantial costs for payers. Clinical trial registration number: NCT03257605.

Molecular Basis of Cancer Pain Management: An Updated Review

Pain can have a significantly negative impact on the quality of life of patients. Therefore, patients may resort to analgesics to relieve the pain. The struggle to manage pain in cancer patients effectively and safely has long been an issue in medicine. Analgesics are the mainstay treatment for pain management as they act through various methods on the peripheral and central pain pathways. However, the variability in the patient genotypes may influence a drug response and adverse drug effects that follow through. This review summarizes the observed effects of analgesics on UDP-glucuronosyl (UGT) 2B7 isoenzyme, cytochrome P450 (CYP) 2D6, μ-opioid receptor μ 1 (OPRM1), efflux transporter P-glycoprotein (P-gp) and ATP-binding cassette B1 ABCB1/multiple drug resistance 1 (MDR1) polymorphisms on the mechanism of action of these drugs in managing pain in cancer. Furthermore, this review article also discusses the responses and adverse effects caused by analgesic drugs in cancer pain management, due to the inter-individual variability in their genomes.

Genetic Variants Associated with Cancer Pain and Response to Opioid Analgesics: Implications for Precision Pain Management

OBJECTIVE

To review the current knowledge on the association of genetic variants with cancer pain.

DATA SOURCES

Data-based publications and review articles retrieved from PubMed, CINAHL, and Web of Science, as well as an additional search in Google Scholar.

CONCLUSION

Genetic variability can influence differential pain perception and response to opioids in cancer patients, which will have implications in the optimal personalized treatment of cancer pain. More studies are warranted to replicate findings.

IMPLICATIONS FOR NURSING PRACTICE

Nurses are poised to educate patients on biomarker testing and interpretation and to use precision pain management strategies based on this information.

Oral prolonged-release Oxycodone-Naloxone: analgesic response, safety profile, and factors influencing the response in advanced cancer patients

BACKGROUND

Oxycodone-Naloxone (OXN) aims to reduce opioid-related constipation while being successfully analgesic.

METHODS

We evaluated the analgesic response, prevalence, and severity of side effects in 176 cancer patients with moderate to severe pain and treated with OXN. Patients were followed for 28 days and evaluated every seven. Pain intensity, changes of therapy, and adverse drug reactions were recorded at each visit. The primary efficacy endpoint was the proportion of responders (≥30% reduction of pain intensity from baseline to final) and final average pain score ≤4 on a 0-10 scale.

RESULTS

Average and worst pain intensity, and breakthrough pain (BTP) prevalence decreased over time and 81.3% of patients were responders. The starting daily dose of OXN was raised from 25.1±13.0 mg to 44.1±29.9 mg, and dose escalation >5%/day was observed in 19.4% of patients; 40.8-46.2% and 11.0-17.0% experienced any and severe grade of constipation during the follow-up visit, respectively. Digestive system tumor, thyroid endocrinopathies, psychological irritability, and BTP increased the risk of analgesic non-response.

CONCLUSIONS

OXN had strong analgesic effect in moderate to severe cancer pain patients: the safety profile is in line with the common adverse effects of opioids and severe constipation was uncommon. This article is protected by copyright. All rights reserved.

Continuing war on pain: a personalized approach to the therapy with nonsteroidal anti-inflammatory drugs and opioids

Successful pain management requires the delivery of analgesia with minimal risk of adverse drug reactions. Nonsteroidal anti-inflammatory drugs and opioids remain the mainstay of treatment for the majority of patients. Unfortunately, almost 50% of all patients experience inadequate pain relief and serious side effects. Allelic variants in genes coding for target proteins, transporters and enzymes, which govern analgesic drugs action and their fate in the organism, might explain inter-individual variability in pain severity and in drug-induced pain relief and toxicities. Additionally, it seems that epigenetic changes contribute to the highly variable response to pain treatment. Therefore, pharmacogenomic testing might be a valuable tool for personalization of pain treatment, with a multidisciplinary team approach involved.

Clinical and pharmacogenetics associated with recovery time from general anesthesia

AIM

Delayed recovery from general anesthesia is a well-known complication that requires predictive tools and approaches. This study aimed to determine significant factors associated with postanesthesia recovery and to develop an algorithm for estimating recovery time from general anesthesia.

MATERIALS & METHODS

The genotypes of patients were determined by SNaPshot or ARMS-qPCR. The algorithm was developed via machine-learning and tested by the worm plot.

RESULTS

Results showed that OPRM1 rs1799971 (p = 0.006) and ABCG2 rs2231142 (p = 0.041) were significantly associated with recovery time. Ten factors after random forest and stepwise selection were associated with recovery time. Ten factors after random forest and stepwise selection were associated with recovery time. Meanwhile, seven factors were associated with delayed recovery.

CONCLUSION

This study demonstrated that both clinical and pharmacogenetic data are significantly associated with recovery from general anesthesia and provide the basis for pre-emptive prediction tools.

The pharmacogenetics of medications used in general anesthesia

General anesthesia is a state of unconsciousness, amnesia, analgesia and akinesia induced by drugs including opioids, hypnotic-sedative agents, muscle relaxants and antiemetics. Clinical and genetic factors are reported to influence the efficacy and side effects of these agents. Based on the evidence, clinical action is needed to improve clinical outcomes. This review summarizes the latest knowledge with regards to the pharmacogenetics of anesthetics and general anesthesia related complications.

Prospective replication study implicates the catechol-O-methyltransferase Val158Met polymorphism as a biomarker for the response to morphine in patients with cancer

Genetic differences in humans cause clinical difficulties in opioid treatment. Previous studies indicate that a single nucleotide polymorphism in the catechol-O-methyltransferase (COMT) gene (rs4680; p.Val¹⁵⁸Met) may present as a predictive biomarker for the response to morphine treatment. In our previous pilot exploratory study, patients with a G/G genotype were demonstrated to require a higher dose of morphine, compared with patients with A/A and A/G genotypes. In the present study, the aim was to replicate the findings in an independent cohort of opioid-treatment-naïve patients exhibiting various types of cancer. This prospective study was conducted from 2011 to 2012 at the Kindai University Faculty of Medicine. A total of 50 patients with opioid-treatment naïve and histologically confirmed malignant neoplasms who were scheduled to undergo opioid treatment were evaluated in the present study. Assessments were conducted pre-treatment (day 1), post-treatment (day 1), and one week after treatment (day 8). The required dose of morphine on day 1 was significantly higher for patients with the G/G genotype of COMT, compared with those with the A/A and A/G genotypes (P=0.013). The results of the present study provide additional evidence that the COMT genotype may be a predictive biomarker for the response to morphine treatment.

Whole exome sequencing detects variants of genes that mediate response to anticancer drugs

Certain interindividual differences affecting the efficacy of drug treatment and adverse drug reactions are caused by genetic variants, and their phenotypic effects differ among ethnic groups. In this study, we used whole exome sequencing (WES) systematically to identify germline mutations that influence the activities of drug-metabolizing enzymes, as well as that of a transporter. We analyzed DNA isolated from blood samples from 2,042 Japanese patients with diverse cancers. We identified sequence variants of CYP2B6 (rs3745274), CYP2C9 (rs1057910), CYP2C19 (rs4986893), CYP2C19 (rs4244285), TPMT (rs1142345), NAT2 (rs1799930), NAT2 (rs1799931), UGT1A1 (rs4148323), COMT (rs4680), ABCB1 (rs1045642), and CDA (rs60369023). Wider application of WES will help to determine the effects of mutations on the activities of proteins encoded by drug response genes, and the information gained will accelerate the development of personalized therapies for patients with cancer. Moreover, this knowledge may provide clues for preventing cancer before the onset of symptoms.

CYP2D6 pharmacogenetic and oxycodone pharmacokinetic association study in pediatric surgical patients

AIM

Oxycodone is partly metabolized to the active metabolite oxymorphone by hepatic CYP2D6 in the liver. Significant genetic variability in CYP2D6 activity affects oxymorphone formation. This study aimed to associate CYP2D6 genotype and oxycodone's metabolism.

METHODS

30 children were administered oral oxycodone postoperatively. Plasma levels of oxycodone and oxymorphone, and CYP2D6 genotype were analyzed. CYP2D6 genotype and oxycodone metabolism phenotype were determined based on CYP2D6 total activity score (TAS) and metabolism phenotype: poor metabolizer (PM), intermediate metabolizer (IM), extensive metabolizer (EM) or ultrarapid metabolizer (UM).

RESULTS

Compared with PM/IM subjects, significantly greater oxymorphone exposure was seen in EM subjects (p = 0.02 for C_max, p = 0.016 for AUC_0-6 and p = 0.026 for AUC_0-24). Similarly, higher TAS value was found to be associated with greater oxymorphone exposure. Higher conversion of oxycodone to oxymorphone was observed in EM subjects compared with PM/IM subjects (p = 0.0007 for C_max, p = 0.001 for AUC_0-6 and p = 0.004 for AUC_0-24).

CONCLUSION

CYP2D6 phenotypes explain metabolism of oxycodone in children, and oxymorphone exposure is higher in CYP2D6 EM phenotype. Further studies are needed to predict the occurrence of adverse event and tailor oxycodone dose for a specific CYP2D6 phenotype.

A Novel Sensitive Method to Measure Catechol-O-Methyltransferase Activity Unravels the Presence of This Activity in Extracellular Vesicles Released by Rat Hepatocytes

There is a clear need for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. One of the main enzymes to take into account in pharmacogenomics is catechol O-methyltransferase (COMT), which catalyzes the transfer of a methyl group from S-adenosylmethionine to catechols and catecholamines, like the neurotransmitters dopamine, epinephrine, and norepinephrine. Although, most of this enzyme is associated to intracellular vesicles, recently it has also been detected in extracellular vesicles secreted by hepatocytes and in serum circulating vesicles. COMT has implications in many neurological and psychiatric disorders like Parkinson's disease, chronic fatigue, pain response, schizophrenia, and bipolar disorders. Remarkably, genetic variations of COMT affect its activity and are associated to various human disorders from psychiatric diseases to estrogen-induced cancers. Consequently, the establishment of new methods to evaluate COMT activity is an important aspect to investigate the biology of this drug-metabolizing enzyme. Herein, we have developed a sensitive and selective method to determine COMT activity. We first optimized the activity in rat liver incubated with two different substrates; norepinephrine and dopamine. The enzymatically formed products (normetanephrine and 3-methoxytyramine, respectively) were extracted by solid-phase extraction using weak cation exchange cartridges, chromatographically separated, and detected and quantified using a mass spectrometer. The range of quantitation for both products was from 0.005 to 25 μg/mL. This methodology offers acceptable recovery for both enzymatic products (≥75%) and good accuracy and precision (≤15%). The lower limit of quantifications were 0.01 and 0.005 μM for 3-methoxytyramine and normetanephrine, respectively. Importantly, this sensitive assay was able to detect the presence of COMT activity in extracellular vesicles secreted by hepatocytes supporting a potential role of these vesicles in catecholamines and catecholestrogens metabolisms. In addition, the presence of COMT activity in extracellular vesicles opens new possibilities to develop tools to evaluate personalized drug response in a low invasive manner.