Consistency of psychotropic drug–drug interactions listed in drug monographs

Background

With an increasing prevalence of psychotropic polypharmacy, clinicians depend on drug–drug interaction (DDI) references to ensure safe regimens, but the consistency of such information is frequently questioned.

Potential drug–drug interactions in internal medicine wards in hospital setting in Pakistan

Background Multiple drugs therapies may be the potential source of drug–drug interactions that can result in alteration of therapeutic response and/or increase untoward effects of many drugs. Objective To identify the frequency and levels of potential drug–drug interactions (pDDIs) in internal medicine wards and their association with patients’ age, gender, length of hospital stay and number of prescribed medications; and to describe management of frequently identified major or moderate pDDIs. Setting Internal medicine wards of two major tertiary care hospitals of Khyber Pakhtunkhwa, Pakistan. Method Micromedex Drug-Reax system was used to screen patient’s profiles for pDDIs. Logistic regression was applied to determine the odds ratio for specific risk factors of pDDIs i.e., age, gender, hospital-stay and number of medications. Main outcome measure Overall prevalence and prevalence of contraindicated, major, moderate and minor pDDIs; levels of pDDIs; frequently identified major or moderate interactions; and odds ratios for risk factors. Results Total, 188 interacting drug-combinations were identified that contributed to 675 pDDIs. Of 400 patients, 52.8 % patients were presented with at least one pDDI (overall prevalence), 21.3 % with at least one major-pDDI, and 44.3 % with at least one moderate-pDDI. Of 675 pDDIs, most were of moderate (63.6 %) or major severity (23 %); good (61.2 %) or fair (25.5 %) type of scientific evidence; and delayed onset (50.2 %). Most frequently identified major or moderate interactions resulted in 45.3 % of all pDDIs. Their potential adverse outcomes included hepatotoxicity, bleeding, ototoxicity, nephrotoxicity, hypoglycemia, hyperglycemia, risk of thrombosis, hypotension, cardiac arrhythmias and reduction in therapeutic-effectiveness. There was significant association of the occurrence of pDDIs with patients’ age of 60 years or more (OR = 2.1; 95 % CI = 1.3–3.3; p = 0.003), hospital stay of 6 days or longer (OR = 2.6; 95 % CI = 1.5–4.5; p = 0.001), and seven or more number of prescribed medications (OR = 5.9; 95 % CI = 3.6–9.6; p < 0.001). Conclusion The present study has recorded a high prevalence of pDDIs in internal medicine wards. Patients with old age, longer hospital stay and increased number of prescribed medications were at higher risk.     

Pharmacokinetic drug–drug interactions with methotrexate in oncology

Methotrexate is an antifolate agent used in the treatment of various cancers and some autoimmune diseases. In oncology, methotrexate is frequently administered at a high dose (>1 g/m²) and comes with various procedures to reduce the occurrence of toxicity and particularly to ensure optimal renal elimination. Drug–drug interactions involving methotrexate are the origin of severe side effects owing to delayed elimination of the antifolate and, more rarely, of decreased efficacy in relation to suboptimal exposure. Most of these interactions are driven by membrane drug transporters whose activity/expression can be inhibited by the interacting medication. In the last 10 years, research on drug transporters has permitted retrospective identification of the molecular mechanisms underlying drug–drug interactions with methotrexate. This article summarizes reported drug–drug interactions involving methotrexate in clinical oncology with reference to the role of drug transporters that control the disposition of the antifolate agent.     

Improvement in the handling of drug–drug interactions

Approximately one in 200 hospitalised patients has a serious adverse drug effect caused by drug–drug interactions (DDIs). Such adverse effects should be avoidable, but current information provided on DDIs is often incomplete and difficult or even impossible to translate into true risk and appropriate tangible action. Clinicians need to know the mean and maximal expected effect of a DDI on clinical endpoints, any dose adjustments required, and how to monitor tolerability and efficacy in patients subject to a DDI. To this end, improved study designs should take the objective of improving treatment explicitly into account, and any existing DDI data should be publicly accessible. Modelling needs to be used more extensively in order to quantitatively predict the effects of DDIs on clinical endpoints in patients and to relate clinical endpoint effects considered as acceptable to respective changes in experimental and clinical studies. Computer-based expert systems will be required to convert such DDI data into recommendations applicable to the individual patient. Therefore, the incorporation of DDIs in a more general procedure for personalisation of drug therapy is desirable.     

Polypharmacy and potential drug–drug interactions in emergency department patients in the Caribbean

Background Potential Drug–Drug Interactions (DDI) account for many emergency department visits. Polypharmacy, as well as herbal, over-the-counter (OTC) and combination medication may compound this, but these problems are not well researched in low-and-middle-income countries. Objective To compare the incidence of drug–drug interactions and polypharmacy in older and younger patients attending the Emergency Department (ED). Setting The adult ED of a tertiary teaching hospital in Trinidad. Methods A 4 month cross sectional study was conducted, comparing potential DDI in older and younger patients discharged from the ED, as defined using Micromedex 2.0. Main outcome measure The incidence and severity of DDI and polypharmacy (defined as the use of ≥5 drugs simultaneously) in older and younger patients attending the ED. Results 649 patients were included; 275 (42.3%) were ≥65 years and 381 (58.7%) were female. There were 814 DDIs, of which 6 (.7%) were contraindications and 148 (18.2%) were severe. Polypharmacy was identified in 244 (37.6%) patients. Older patients were more likely to have potential DDI (67.5 vs 48.9%) and polypharmacy (56 vs 24.1%). Herbal products, OTC and combination drugs were present in 8, 36.7 and 22.2% of patients, respectively. On multivariate analysis, polypharmacy and the presence of hypertension and ischaemic heart disease were associated with an increased risk of potential DDI. Conclusion Polypharmacy and potential drug–drug interactions are common in ED patients in the Caribbean. Older patients are particularly at risk, especially as they are more likely to be on multiple medications. The association between herbal medication and polypharmacy needs further investigation. This study indicates the need for a more robust system of drug reconciliation in the Caribbean.     

Potential drug–drug interactions in medical intensive care unit of a tertiary care hospital in Pakistan

Background Patients admitted to intensive care unit (ICU) present with severe and life-threatening illnesses. Most of them suffer from various comorbidities. They usually receive complex pharmacotherapy with large number of medicines which increase the risk of drug–drug interactions (DDIs). Objective The present report aimed to investigate prevalence and levels of potential DDIs (pDDIs) in medical ICU. Methods Medications profiles of 416 patients were checked for pDDIs using Micromedex Drug-Reax^®. Prevalence, levels of severity and levels of documentation were reported. Results Of total 416 patients, 310 were exposed to pDDIs (overall prevalence = 74.5 %). Likewise, a prevalence rate of 13.9 % was recorded for contraindicated pDDIs, 52.2 % for major pDDI and 58.4 % for moderate pDDI. This study reported 740 interacting drug pairs that were presented in total 1686 pDDIs. Of 1686 pDDIs, 4.3 % were of contraindicated severity, 33.8 % of major severity and 49.6 % of moderate severity, whereas 45.5 % were of fair scientific evidence and 41.4 % of good scientific evidence. Conclusion In this study, pDDIs were found highly prevalent in ICU patients at a rate of 74.5 %. Most of the pDDIs had moderate severity; however, substantial number of interactions (38.1 %) had major and contraindicated severity.     

Clinical utility of drug measurement and pharmacokinetics – therapeutic drug monitoring in psychiatry

Based on the assumption that a relationship between blood levels and clinical effects (therapeutic effects, adverse events and toxicity) can be defined and considering that after equal doses plasma concentrations vary markedly between individual patients, therapeutic drug monitoring (TDM) can assist to personalize dose adjustment. Taken together, drug levels and a knowledge of the pharmacological profile of the administered drugs can enable the optimal dosage to be tailored according to the need of the individual patient. Therapeutic drug monitoring has been established for a limited number of drugs. In psychiatry, it has a 40-year-long history, which started with nortriptyline. Evidence has accumulated which shows that TDM is a valid tool for the optimization of psychopharmacotherapy. When used adequately, TDM is helpful for many patients and in many situations. Combined with pharmacogenetic tests, the metabolic status of a patient can be well characterized. Several new observations have been made during routine TDM that have stimulated clinical pharmacological research, such as investigations on inherited differences in drug metabolism that are closely linked to TDM in psychiatry. The contributions of individual forms of cytochrome P450 (CYP) to the metabolism of drugs was elicited by clinical observations on pharmacokinetic drug interactions. Therapeutic drug monitoring requires a close collaboration between the prescribing physician, the laboratory specialist, the clinical pharmacologist and the patient. This complexity may result in errors which can be detected by analysing the appropriate use of TDM in clinical practice. More education has to be provided to the prescribing clinicians on the pharmacology of the drugs and the algorithm of TDM. Moreover, clinical trials should include measurements of blood concentrations during drug development to generate valid data on the relationships between drug concentrations and clinical outcomes under well-controlled conditions. This would merely increase the amount of work and costs, as high-throughput methods are now available in many laboratories. Any progress in TDM has direct benefits for the treatment of many individual patients.     

Patient- and physician-related risk factors for hyperkalaemia in potassium-increasing drug–drug interactions

Purpose

Hyperkalaemia due to potassium-increasing drug–drug interactions (DDIs) is a clinically important adverse drug event. The purpose of this study was to identify patient- and physician-related risk factors for the development of hyperkalaemia.

Methods

The risk for adult patients hospitalised in the University Hospital Zurich between 1 December 2009 and 31 December 2011 of developing hyperkalaemia was correlated with patient characteristics, number, type and duration of potassium-increasing DDIs and frequency of serum potassium monitoring.

Results

The 76,467 patients included in this study were prescribed 8,413 potentially severe potassium-increasing DDIs. Patient-related characteristics associated with the development of hyperkalaemia were pulmonary allograft [relative risk (RR) 5.1; p?<?0.0001), impaired renal function (RR 2.7; p?<?0.0001), diabetes mellitus (RR 1.6; p?=?0.002) and female gender (RR 1.5; p?=?0.007). Risk factors associated with medication were number of concurrently administered potassium-increasing drugs (RR 3.3 per additional drug; p?<?0.0001) and longer duration of the DDI (RR 4.9 for duration ≥6 days; p?<?0.0001). Physician-related factors associated with the development of hyperkalaemia were undetermined or elevated serum potassium level before treatment initiation (RR 2.2; p?<?0.001) and infrequent monitoring of serum potassium during a DDI (interval >48 h: RR 1.6; p?<?0.01).

Conclusion

Strategies for reducing the risk of hyperkalaemia during potassium-increasing DDIs should consider both patient- and physician-related risk factors.     

Assessing the potential for drug–drug interactions in an accelerated throughput mode

Drug candidates that cause pharmacokinetic drug drug interactions are less likely to become a commercial success. However, rapid, cost-effective, mechanism-based screens are available for the evaluation of the potential of drug candidates to cause drug&ndashdrug interactions. This review describes experimental designs for, and recent progress in, increasing the throughput of these screens.     

Application and prospect of drug discrimination in field of drug abuse北大核心CSCD

药物辨别技术是一种研究药物主观刺激效应的行为药理学技术。目前,药物辨别技术已广泛应用于中枢神经系统药物临床前药物研发中,其中最为广泛的是用于药物的精神依赖性评价。该文简要介绍了药物辨别技术的基本原理,初步阐述了药物辨别的主观效应、时程效应、立体特异性和个体差异,以及受体机制等相关特点和应用,并对其在新型精神活性物质致幻剂和大麻类药物方面的应用进行展望。     

Clinical disposition,metabolism and in vitro drug–drug interaction properties of omadacycline

1.?Absorption, distribution, metabolism, transport and elimination properties of omadacycline, an aminomethylcycline antibiotic, were investigated in vitro and in a study in healthy male subjects.

2.?Omadacycline was metabolically stable in human liver microsomes and hepatocytes and did not inhibit or induce any of the nine cytochrome P450 or five transporters tested. Omadacycline was a substrate of P-glycoprotein, but not of the other transporters.

3.?Omadacycline metabolic stability was confirmed in six healthy male subjects who received a single 300?mg oral dose of [¹⁴C]-omadacycline (36.6 μCi). Absorption was rapid with peak radioactivity (～610 ngEq/mL) between 1–4?h in plasma or blood. The AUC_last of plasma radioactivity (only quantifiable to 8?h due to low radioactivity) was 3096 ngEq?h/mL and apparent terminal half-life was 11.1?h. Unchanged omadacycline reached peak plasma concentrations (～563?ng/mL) between 1–4?h. Apparent plasma half-life was 17.6?h with biphasic elimination. Plasma exposure (AUC_inf) averaged 9418?ng?h/mL, with high clearance (CL/F, 32.8?L/h) and volume of distribution (Vz/F 828?L). No plasma metabolites were observed.

4.?Radioactivity recovery of the administered dose in excreta was complete (>95%); renal and fecal elimination were 14.4% and 81.1%, respectively. No metabolites were observed in urine or feces, only the omadacycline C4-epimer.     

Human hepatocyte assessment of imatinib drug–drug interactions – complexities in clinical translation

Aim

Inducers and inhibitors of CYP3A, such as ritonavir and efavirenz, may be used as part of the highly active antiretroviral therapy (HAART) to treat HIV patients. HIV patients with chronic myeloid leukemia or gastrointestinal stromal tumour may need imatinib, a CYP3A4 substrate with known exposure response–relationships. Administration of imatinib to patients on ritonavir or efavirenz may result in altered imatinib exposure leading to increased toxicity or failure of therapy, respectively. We used primary human hepatocyte cultures to evaluate the magnitude of interaction between imatinib and ritonavir/efavirenz.

Methods

Hepatocytes were pre-treated with vehicle, ritonavir, ketoconazole, efavirenz or rifampicin, and the metabolism of imatinib was characterized over time. Concentrations of imatinib and metabolite were quantitated in combined lysate and medium, using LC-MS.

Results

The predicted changes in imatinib CL_oral (95% CI) with ketoconazole, ritonavir, rifampicin and efavirenz were 4.0-fold (0, 9.2) lower, 2.8-fold (0.04, 5.5) lower, 2.9-fold (2.2, 3.5) higher and 2.0-fold (0.42, 3.5) higher, respectively. These predictions were in good agreement with clinical single dose drug–drug interaction studies, but not with reports of imatinib interactions at steady-state. Alterations in metabolism were similar after acute or chronic imatinib exposure.

Conclusions

In vitro human hepatocytes predicted increased clearance of imatinib with inducers and decreased clearance with inhibitors of CYP enzymes. The impact of HAART on imatinib may depend on whether it is being initiated or has already been dosed chronically in patients. Therapeutic drug monitoring may have a role in optimizing imatinib therapy in this patient population.     

CNS drug development - lost in translation?

CNS drug development is characterized by an especially high attrition rate, despite clear unmet medical needs in the field of neuro-pharmacology and significant investment in R of novel CNS drug treatments. Here, we overview the issues underlying the intrinsic difficulty of CNS drugs development, including obstacles of pharmacokinetic nature and lack of predictivity of preclinical tests. We highlight current efforts to overcome these limitations, with an emphasis on modeling opportunities towards early recognition of CNS candidates (stressing the possibilities of multi-target directed ligands or "magic shotguns") and different approaches to improve CNS bioavailability.