Problematic polypharmacy is a growing challenge. Medication that is intended to improve patients’ health and wellbeing is instead becoming part of the problem. The way we practice medicine has become one of the drivers for the problems. Dealing with the challenge will need us to think differently about how we do clinical care. A 2013 Kings Fund report stated that tackling problematic polypharmacy requires us to actively build a principle of ‘compromise’ in to the way we use medicines. There are implications for how we consult and make decisions with patients, in how we design health practice and systems to support that decision making, and in our understanding of the process of research – how we generate the knowledge that informs practice. This review considers the current state of play in all three areas and identifies some of the work still need to do in order to generate the practice-based evidence needed to tackle this most challenging problem. Finding a way to redesign practice to address problematic polypharmacy could offer a template for tackling other related complex issues facing medical practice such as multimorbidity, chronic pain and complex mental health.

Aims: To assess the appropriateness of the use and interpretation of subgroup analysis in haematology randomized clinical trials (RCT). Method: A systematic review of Medline including Haematology phase III RCT published between January 2013 and October 2019 was carried to identify subgroup analysis reported. Information related to trials characteristics, subgroup analysis reported and claims of subgroup difference were collected. Results: A total of 98 studies reporting subgroup analyses were identified. Of those, 24 RCT reported 46 claims of subgroup difference. Among them, 44 were claims for the primary outcome, of which 25 were considered strong claims and 17 were considered suggestions of a possible effect. Authors included subgroup variables for the primary outcome measured at baseline for 38 claims (n = 86.36%), used subgroup variable as stratification factor at randomization for 15 (34.09%), clearly prespecify their hypothesis for 11 (25%), the subgroup effect was one of a small number of hypothesised effects tested for 17 (38.36%), carried out a test of interaction that provide statistically significant for 18 (40.91%), documented replication of a subgroup effect with previously related studies for 11 (25%), identify consistency of a subgroup effect across related outcome for 10 (22.72%), and provided a biological rationale for the effect for 8 (18.18%). Of the 44 claims for the primary outcome, 34 (77.27%) met 4 or fewer of the 10 credibility criteria. Conclusion: Credibility of subgroup claims reported in haematology RCT lack of credibility, even when claims are strong. Information about subgroup difference should be interpreted ca

Mitotane is the only drug approved for treating adrenocortical carcinoma (ACC) by the FDA since 1959, despite the controversy regarding its efficacy in prolonging patient survival. This drug has cytotoxic effects on tumor tissue by inducing cell death and antisecretory effects on adrenal cells by inhibiting the synthesis of adrenocortical steroids involved in the pathogenesis of ACC. To reach the therapeutic plasma concentration, high doses of mitotane are usually necessary, which may result in several adverse effects. This suggests that important pharmacological features are involved in the mechanisms of action of this drug, such as first pass metabolism, tissue accumulation, and extensive time needed for drug elimination. However, few studies have reported the pharmacological aspects of mitotane, and they did not provide sufficient evidence regarding monitoring mitotane’s therapeutic effects. Therefore, this review summarized the chemistry, pharmacokinetics and pharmacodynamics, therapeutic effects, toxic effects, and new perspectives of mitotane treatment that are currently under investigation. Understanding the pharmacological profile of mitotane can improve the monitoring and efficacy of this drug in ACC treatment and can further provide useful information for the development of new drugs with specific action against ACC with fewer adverse effects.

Diffuse Large B-Cell Lymphoma is the most common type of Non-Hodgkin’s Lymphoma. The disease exhibits significant clinical and biologic heterogeneity. Treatment with standard first line therapy results in cure in about 60% of patients while 30-40%of patients either are refractory to therapy or relapse. Current prognostic scores and biomarkers are unable to accurately predict patients who would relapse or would have refractory disease. A part of the heterogeneity in the behavior of DLBCL is explained by the cell of origin of the tumor. Germinal center type (GCB) DLBCL which is derived from centroblasts are associated with better prognosis compared with activated B-cell type (ABC), which is derived from a B-cell committed to secretory differentiation. While the gold standard for cell of origin determination is gene expression profiling, immunohistochemical methods are routinely used because of more readily available fixed tissue and expertise. Immunohistochemical methods are however associated with a significant degree of discordance with GEP. Within the ABC and GCB types of DLBCL, subgroups of prognostic significance have been identified using various multiple approaches which do not inure themselves to routine practice partly because of limitation of diagnostic material or expertise. Exosomes are a class of membrane bound extracellular vesicles of endosomal origin, produced by multiple cell types. They are involved in intercellular communication and present in abundance in various bodily fluids. Exosomal cargo which includes nucleic acids and proteins can be analyzed, yielding diagnostic and prognostic information in management of DLBCL.

Aims: To assess whether randomized clinical trials (RCTs) proposed to evaluate treatment of COVID-19 with HQ or chloroquine include outcome definitions and data collection plans to produce meaningful efficacy/effectiveness and safety outcomes. Methods: We searched the World Health Organization International Clinical Trials Registry Platform (WHO-ICTRP) database for registers of RCTs evaluating HQ or chloroquine, alone or in any combination, to treat patients diagnosed with COVID-19 compared with any other treatment option. The final search was performed on April 8th, 2020. Results: Among 51 registered RCTs (median sample size of 262; IQR: 100, 520), 34 (67%) reported a clinical outcome, 12 (24%) a surrogate outcome, and five (10%) a combination of clinical and surrogate outcomes as primary endpoints. Clinical status/recovery and all-cause mortality/mortality accounted for 49% of the unique domains among 20 different clinical outcome domains of efficacy. Twenty-four (47%) RCTs did not describe plans to assess safety outcomes; when assessed, safety outcomes were determined in generic terms of total, severe or serious adverse events. Conclusions: The RCTs investigating HQ or chloroquine include heterogenous and insufficient approaches to measure efficacy/effectiveness and safety that are relevant to patients and clinical practice. These findings provide important insights to inform clinical and regulatory decisions that can be drawn about the efficacy/effectiveness and safety of these agents in patients with COVID-19.

Aim To assess clinical outcomes and adverse drug events in patients hospitalised with COVID -19 treated with off- label hydroxychloroquine and azithromycin. Methods We performed a retrospective analysis of hospitalised COVID-19+ patients who received hydroxychloroquine plus azithromycin over a 2 week period. The primary end point was clinical improvement on day 7 defined as either hospital discharge or an improvement of two points on a six-category ordinal scale. Secondary outcomes evaluated included mortality at day 28, ICU admission, requirement for mechanical ventilation and incidence of adverse drug events. Results Data from a total of 82 patients with laboratory confirmed SARS-CoV-2 infection was evaluated. Clinical improvement was seen in 26.8% of patients at Day 7. 31% of patients were admitted to ICU, 16 (19.5%) underwent mechanical ventilation and Day 28 mortality was 28%. Age over 70, history of cardiovascular disease and 3 or more comorbidities were risk factors for mortality. The incidence of adverse drug events was 42%. No patient experienced a Grade 4 or 5 toxicity. Over a fifth of patients (23) had raised LFTs (65% had raised LFTs at baseline), 11 patients experienced prolonged QT and 1 patient experienced grade 1 hypoglycaemia. Treatment was stopped early in 6(7.3%) patients due to prolonged QT interval or LFT elevations. Conclusion This descriptive study details the clinical outcomes of COVID-19 positive patients treated with these agents and highlights the importance of monitoring all repurposed agents for adverse drug events.

Aims The field of cell-based therapies for human diseases is currently evolving from promising treatment options to established therapeutic concepts. The design of the non-clinical development program for cell-based products, intended to provide a rationale for treatment and to gain insight into the safety profile, is challenging because of limitations caused by species-specificity. The elements of the non-clinical package for cell-based products were evaluated using advice reports from the European Medicines Agency database from 2013-2018 to identify the approach followed for non-clinical development of these products. Methods The purpose of the in vivo studies was designated to be (a combination of) pharmacology/proof-of-concept, safety, biodistribution and/or tumourigenicity. For biodistribution and tumourigenicity also the need for, type and design of in vitro and in vivo studies were recorded. Results In vivo studies for cell-based therapies were primarily aimed at proof-of-concept (75/86), followed by addressing safety (64/86), biodistribution (49/86) or tumourigenicity (46/86). No animal studies were performed or proposed by sponsors or regulators for six (out of 86) products, which contained cell types that have been studied in humans for a relatively long time. For one-third of the products in vivo biodistribution and/or tumourigenicity studies were not considered necessary. In vivo tumourigenicity studies were regarded of limited value. Conclusions Compared to more conventional medicinal products, the non-clinical development program for cell-based products was more tailored and focussing on proof-of-concept. For tumourigenicity an in vitro approach may suffice. Total omission of in vivo studies appears to be possible for products with sufficient clinical experience.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been declared a global pandemic and urgent treatment and prevention strategies are needed. Nitazoxanide, an anthelmintic drug has been shown to exhibit in vitro activity against SARS-CoV-2. The present study used physiologically-based pharmacokinetic (PBPK) modelling to inform optimal doses of nitazoxanide capable of maintaining plasma and lung tizoxanide exposures above the reported nitazoxanide SARS-CoV-2 EC90. Methods: A whole-body PBPK model was validated against available pharmacokinetic data for healthy individuals receiving single and multiple doses between 500–4000 mg with and without food. The validated model was used to predict doses expected to maintain tizoxanide plasma and lung concentrations above the nitazoxanide EC90 in >90% of the simulated population. PopDes was used to estimate an optimal sparse sampling strategy for future clinical trials. Results: The PBPK model was successfully validated against the reported human pharmacokinetics. The model predicted optimal doses of 1200 mg QID, 1600 mg TID, 2900 mg BID in the fasted state and 700 mg QID, 900 mg TID and 1400 mg BID when given with food. For BID regimens an optimal sparse sampling strategy of 0.25, 1, 3 and 12h post dose was estimated. Conclusion: The PBPK model predicted tizoxanide concentrations within doses of nitazoxanide already given to humans previously. The reported dosing strategies provide a rational basis for design of clinical trials with nitazoxanide for the treatment or prevention of SARS-CoV-2 infection.

Background Adverse drug reactions (ADRs) constitute major clinical burden of public health concern. Intensive adverse drug reactions monitoring in hospitals, though advocated are rare. Aims Intensive monitoring of medical patients for ADRs to assess incidence, risk factors and fatality of ADRs leading to hospital admission or occurring in the hospital. Research design and methods Prospective cohort study on 1280 adult patients admitted to the six medical wards of a tertiary institution over a 12-month period. Patients were assessed for ADRs during and throughout admission. Causality assessment and preventability of ADRs were assessed. Results Sixty-seven (5.2%) patients had ADRs, which was the cause of admission in 46 (3.6%), and majority 61(91%) of the ADRs were preventable. NSAIDs, 14 (20.3%), antidiabetics, 12 (17.4%) and antibacterial, 11 (15.8%) were the most suspected drugs. Gastrointestinal tract (37%), CNS (30.2%), and skin (24.7%) were the most affected organ/systems, while upper GI bleeding and hypoglycaemia were the most observed ADRs. ADRs led to deaths in 7(10.4%) patients, with overall case fatality rate of 0.5%. Stevens-Johnson Syndrome/Toxic Epidermal Necrolysis 3/7(42.9%) had the highest fatality rate. Risk factors, relative risk, 95% confidence interval for ADRs were alcohol intake, 1.7 (1.04, 2.80) and duration of hospital stay, 2.0 (1.16, 3.26). Conclusions Preventable ADRs are common and important cause of hospitalization and inpatients’ morbidity and mortality among medical patients in Nigeria. Upper GI bleeding and hypoglycaemia, resulting from NSAIDs and antidiabetic drugs were the most observed ADRs. Strategic planning for intensive follow up of ADRs in Nigeria is advocated.

Commentary: Animal free applications in the development of cell-based therapies

Aims: Develop a population pharmacokinetic model describing propofol pharmacokinetics in (pre)term neonates and infants, that can be used for precision dosing of propofol in this population. Methods: A non-linear mixed effects pharmacokinetic analysis (Monolix 2018R2) was performed, based on a pooled study population in 107 (pre)term neonates and infants. Results: 836 blood samples were collected from 66 (pre)term neonates and 41 infants originating from three studies. Body weight (BW) of the pooled study population was 3.050 (0.580 – 11.440) kg, postmenstrual age (PMA) was 36.56 (27.00 – 43.00) weeks and postnatal age (PNA) was 1.14 (0 – 104.00) weeks (median and range). A three compartment structural model was identified and the effect of BW was modeled using fixed allometric exponents. Elimination clearance maturation was modeled accounting for the maturational effect on elimination clearance until birth (by GA) and postpartum (by PNA/GA). The extrapolated adult (70 kg) population propofol elimination clearance (1.63 L min-1) is in line with estimates from previous population pharmacokinetic studies. Empirical scaling of BW on the central distribution volume (V1) in function of PNA improved the model fit. Conclusions: It is recommended to describe elimination clearance maturation by GA and PNA instead of PMA on top of size effects when analyzing propofol pharmacokinetics in populations including preterm neonates. Changes in body composition in addition to weight changes or other physio-anatomical changes may explain the changes in V1. The developed model may serve as a prior for propofol dose finding in (preterm) neonates.

AIM: The main objective was to determine the prevalence of prescribing issues in HIV-infected subjects ≥65 years according to the Beers and STOPP/START criteria and drug-drug interactions (Liverpool website). Secondary objectives were to assess the concordance between Beers and STOPP/START criteria in our population, and to identify the drugs most frequently involved in the prescribing issues. METHODS: Cross-sectional cohort study based on a systematic review of the electronic drug prescriptions of 91 HIV-infected patients aged ≥65 years. Discrepancies between prescription criteria were assessed using crosstabs and compared using the Chi-square test or Fisher exact test. RESULTS: The mean age was 72.1 (5.6) years, 75.8% had ≥3 comorbidities, and 59.3% polypharmacy. Prescribing issues were identified in 87.9%; 71.4% by STOPP/START and 45.1% by Beers. Comparing both criteria, 56.9% of prescribing issues by STOPP/START were detected by Beers, while 92.5% of those detected by the Beers criteria were detected by STOPP/START (p<0.001). Orange/red flag interactions were found in 45.1%: 3 severe (red) in 2 patients (2.2%). The most frequent drugs involved in prescribing issues were benzodiazepines (>30%). Cobicistat was the drug most frequently involved in interactions (42.9%). CONCLUSIONS: The prevalence of prescribing issues among older HIV-infected persons gives cause for concern, as it is almost 90%. Optimization strategies, including a critical review of the treatment plan, should be implemented in clinical routine by a multidisciplinary team, in particular in patients with multiple comorbidities and polypharmacy. The STOPP/START criteria should be recommended for European populations, since they seem to better detect prescribing issues.

Aims: The investigation regarding the clinical significance of programmed cell death protein-1 (PD-1)-targeted immunotherapy in Chinese patients is rare. This study evaluated safety and efficacy of PD-1 with Toripalimab, Camrelizumab or Sintilimab for Chinese Hepatocellular carcinoma (HCC) patients in a real-life cohort. Methods: We retrospectively analyzed HBV associated HCC patients treated with Toripalimab, Camrelizumab or Sintilimab in a retrospective cohort from Nov 2018 to Dec 2019. Efficacy was evaluated with objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), time to tumor progression (TTP) and overall survival (OS). Results: Seventy eight patients were finally included in the analysis: 26 for Toripalimab, 36 for Camrelizumab, and 16 for Sintilimab. Mean duration of follow-up was 22.7 ± 12.6 weeks and the mean Cycles of PD-1 at cut-off were 4.8 ± 2.7 for all patients. The ORR and DCR for the whole cohort were 17.9% and 73.1%, respectively. Overall, 21 (26.9%) patients had radiological disease progression and 6 (7.7%) patients died during follow-up. Median PFS was 40.7 (95% CI, 34.7-46.7) weeks, median TTP was 45.7 (95% CI, 40.5-60.0) weeks, and median OS was 51.1 (95% CI, 46.4-55.9) weeks. Most frequent drug-related AEs were Rash (19.2%), Hypertension (15.4%), Fatigue (12.8%), Paraesthesia (12.8%), and Diarrhoea (10.3%). Conclusions: Our findings suggest that: 1. PD-1-targeted immunotherapy with Toripalimab, Camrelizumab or Sintilimab yielded a promising outcome in Chinese HBV patients with HCC; 2. Immunotherapy was well tolerated generally and had manageable side effects, which is worth of popularization and application in clinical practice.

Aims This study aimed to explore the relationship between voriconazole trough concentration (Ctrough) and toxicity, identify the factors significantly associated with voriconazole pharmacokinetic parameters and propose an optimised dosing regimen for patients with liver dysfunction. Methods The study prospectively enrolled 51 patients with 272 voriconazole concentrations. Receiver operating characteristic (ROC) curves were used to explore the relationship between voriconazole Ctrough and toxicity. The pharmacokinetic data was analysed with nonlinear mixed-effects method. Dosing simulations stratified by TBIL (TBIL-1: TBIL < 51 μmol/L; TBIL-2: 51 μmol/L ≤ TBIL < 171 μmol/L; TBIL-3: TBIL ≥ 171 μmol/L) were performed. Results ROC curve analysis revealed that voriconazole Ctrough of ≤ 5.1 mg/L were associated with significantly lower the incidence of adverse events. A one-compartment pharmacokinetic model with first-order absorption and elimination was used to describe the data. Population pharmacokinetic parameters of clearance (CL), the volume of distribution (V) and oral bioavailability (F) were 0.88 L/h, 148.8 L and 88.4%, respectively. Voriconazole CL was significantly associated with total bilirubin (TBIL) and platelet count. The V increased with weight. Patients with TBIL-1 could be treated with loading dose of 400 mg every 12 hours (q12h) for first day and maintenance dose of 100 mg q12h intravenously or orally. TBIL-2 and TBIL-3 patients could be treated with loading dose of 200 mg q12h and maintenance doses of 50 mg q12h or 100 mg once daily (qd) and 50 mg qd orally or intravenously, respectively. Conclusions TBIL-based dosing regimens provide a practical strategy for voriconazole maximizing treatment outcomes.

Quantitative systems pharmacology (QSP) is a relatively new discipline within modelling and simulation that has gained wide attention over the past few years. The application of QSP models spans drug-target identification and validation, through all drug development phases as well as clinical applications. Due to their detailed mechanistic nature, QSP models are capable of extrapolating knowledge to predict outcomes in scenarios that have not been tested experimentally making them an important resource in experimental and clinical pharmacology. However, these models are complicated to work with due to their size and inherent complexity. This makes many applications of QSP models for simulation, parameter estimation and trial design computationally intractable. A number of techniques have been developed to simplify QSP models into smaller models that are more amenable to further analyses while retaining their accurate predictive capabilities. Different simplification techniques have different strengths and weaknesses and hence different utilities. Understanding the utilities of different methods is essential for selection of the best method for a particular situation. In this paper, we have created an overall framework for model simplification techniques that allows a natural categorisation of methods based on their utility. We provide a brief description of the concept underpinning the different methods and example applications. A summary of the utilities of methods is intended provide a guide to modellers in their model endeavours to simplify these complicated models.

Drug therapy in pregnancy may cause anxiety to both physicians and patients due to uncertainty regarding dosing and safety. Nevertheless, the need for medication is high given that maternal chronic illnesses such as hypertension or diabetes are on the rise1. In a national study in the United States over 33 years, the prevalence of prescription medication use by pregnant women in the first trimester increased by 62.5% between the first 2 years of the study and the last 2 years2. Furthermore, the average number of medications used anytime in pregnancy has increased two-fold 2. More recent research from different countries has found that medications are widely used in pregnancy, with the prevalence of using at least one drug ranging from 60 to 90 percent, excluding vitamins and minerals 3-5. Prescription of drugs with potential teratogenicity has also increased in pregnancy, including folate antagonists or angiotensin converting enzyme inhibitors3,4. This suggests that many women go into pregnancy with chronic conditions that require medications, including those may pose some degrees of risk to the fetus, since the maternal benefit may outweigh the risk or if the pregnancy is unplanned. Successful treatment of pregnant patients requires a correct diagnosis and providing treatment that not only is effective but also balances risks and benefits, as maternal health is the best defense for fetal health. However, concomitant health conditions, and the intrinsic complex physiological changes associated to pregnancy can make prescribing in this population a particularly challenging balancing act. Very few drugs have specific pregnancy dosing regimens supported by scientific evidence in spite of well-known pharmacokinetics changes during pregnancy affecting a large proportion of medications (Table 1)6-10. Data on drug efficacy and safety is sorely lacking for pregnant women, even for drugs that have been available for decades. Pregnant patients are commonly excluded from clinical trials during the drug development process due to ethical and safety concerns, which implies that the majority of drug therapy data in pregnancy have been extrapolated from males and to a much lesser extent, from non-pregnant females11. However, using extrapolated data in pregnancy has a number of major drawbacks such as that the extrapolation commonly fails to account for the changes in drug metabolism related to pregnancy 6. Multiple physiological changes in pregnancy, including those affecting pharmacokinetics, must be considered when prescribing. Furthermore, these changes can also be affected by genetic variability10. Some drugs need to be used at higher doses in pregnancy due to increasing metabolic demand. A classic example is thyroid hormone, which requires a 30 to 45 percent higher dose in order to maintain euthyroid state due to limited compensation in pregnant patients with underlying thyroid disease 12. One of the biggest physiologic changes in pregnancy is the expansion of plasma volume by approximately 50 percent due to hormone-mediated vasodilation, leading to activation of the renin-angiotensin-aldosterone system10. This change results in and increased volume of distribution for hydrophilic drugs and reduced peak concentrations 6. Increased glomerular filtration rate in pregnancy also increases elimination of renally cleared drugs; a classic example of this effect is lithium13. Changes in hepatic enzyme activity in pregnancy, including upregulation of cytochrome P450 and glucuronidation, are another cause of increased metabolism and elimination of drugs14. Increased metabolism of lamotrigine by glucuronidation results in low drug levels in pregnancy and this can be further affected by polymorphism of UDP-glucuronosyltransferases 15. One strategy to address changes in drug metabolism is to use therapeutic drug monitoring (TDM) with blood levels; however, TDM analysis is not readily available for the majority of drugs used in pregnancy, limiting the usefulness of this strategy in clinical practice. Furthermore, lower total drug levels do not necessarily translate to less free drug due to volume expansion in pregnancy leading to relative hypoalbuminemia 6. For some drugs, many clinicians modify the dosing regimen on their own based on limited pharmacokinetic data. For example, labelatol, a common antihypertensive used in pregnancy, has a half-life of only 1.7 ± 0.27 hours in patients in the 3rd trimester of pregnancy, compared to 6-8 hours outside of pregnancy16. This difference leads many clinicians to prescribe labelatol three times per day based on patient response instead of twice-per-day as per drug monograph16. However, there is considerable variation among clinicians due to lack of scientific evidence. For example, in patients diagnosed with acute pulmonary embolism, twice-per-day dosing and once-per-day dosing of low molecular weight heparin are both commonly used 17. Enoxaparin once-per-day versus twice-per-day in a population pharmacokinetics study both achieved target plasma concentration in pregnancy18; however, once daily regimen has not been universally adopted in clinical practice and no similar data are available for other low molecular weight heparins. Pregnancy is also a vulnerable period for the occurrence of cardiac events. In particular consideration must be given to patients known to have long QT syndrome or on QT prolonging drugs. The adrenergic nature of labor and delivery may lead to catecholaminergic polymorphic ventricular tachycardia in these patients. Furthermore, patients with congenital long QT syndrome are also at risk during a nine-month post-partum period 19. Treatment with beta-blockers are the mainstay of therapy during pregnancy and in the post-partum period19. There is a lack of data for therapeutics that may be urgently needed intrapartum that may prolong the QT interval in susceptible patients. For example, oxytocin and carbetocin are both known to prolong the QT interval but may be required for prevention or treatment of postpartum hemorrhage20,21. Clinical guidelines for using oxytocin for augmentation or induction of labour are lacking and some obstetricians may choose to do an elective Caesarian section to avoid prolonged oxytocin in these patients although this is not evidence based due to lack of studies. In addition to the challenges in proper prescribing in pregnancy, the information on teratogenicity of drugs is also limited. Management of the care of a pregnant patient must balance the benefits of treating the maternal medical condition with possible adverse effects on the fetus. Clinicians must rely on animal data, data from pregnancy registries, and published case control studies and case reports to make these risk/benefit assessments. These resources are by no means ideal as results are confounded by recall bias, selection bias, and inconsistency, as well as lack of ability to extrapolate safety between species 22. Other than a few specific drugs with clear evidence of harm, many drugs have limited information, leading to variable practice among clinicians and inconsistent information provided to patients. For example, while angiotensin-converting enzyme inhibitor induced fetopathy has been described since the 1990s and accepted by medical community consistently23, the risk of maternal corticosteroid use with increased risk of cleft lip and palate has not been consistent among studies24,25. In addition, long term corticosteroid use is also linked to increased risk of preeclampsia which needs to be taken into consideration for treatment and monitoring26. The US Food and Drug Administration recognized the limitation of the prior FDA classifications for medication use in pregnancy (A, B, C, D, X category system). Thus, the “Pregnancy and Lactation Labeling Rule” went into effect by the FDA in June 2015, requesting manufacturers to provide available information regarding risks in pregnancy and lactation in a narrative summary; however, according to a recent survey, less than 50 percent of prescribers were aware of this change, while more than half deemed the narrative summary not helpful 27. Lack of quality data is one of the barriers identified in this survey. In addition to the rating systems used in various jurisdictions, an evidence-based medicine classification system has been developed by toxicologists, which can be used to assist clinical decision making. Unfortunately, all of the currently available systems are of limited utility due to reliance on small studies and inability to be updated frequently with new data22. Since the thalidomide story in the 1960s, much advancement has been made in medical therapy in pregnant women. However there remains a significant knowledge gap in pharmacological information which may expose patients to either toxicity or under treatment with reduced efficacy. In addition, numerous commonly used medications lack concrete data on teratogenicity. Supported by the NIH, the Pediatric Trials Network is currently conducting a multicentre trial studying the pharmacokinetics and safety of commonly used drugs in lactating women and breastfeeding infants in North America (NCT03511118); similar studies in pregnancy are also warranted to guide appropriate dosing. Long term data on children with fetal exposure for developmental toxicity are also urgently needed, and while some data for newer medications is systematically collected by international registries, in general information on fetal risks of maternal exposures is limited to incidental data obtained from accidental exposures. Finally, making all up-to-date information readily available to clinicians should also be a priority. References1. Sun AJ, Li S, Zhang CA, Jensen TK, Lindahl-Jacobsen R, Eisenberg ML. Parental comorbidity and medication use in the USA: a panel study of 785 000 live births. Hum Reprod.Mar 18 2020.2. Mitchell AA, Gilboa SM, Werler MM, et al. Medication use during pregnancy, with particular focus on prescription drugs: 1976-2008. American journal of obstetrics and gynecology. Jul 2011;205(1):51 e51-58.3. Ventura M, Maraschini A, D’Aloja P, et al. Drug prescribing during pregnancy in a central region of Italy, 2008-2012. BMC Public Health. May 15 2018;18(1):623.4. Engeland A, Bjorge T, Klungsoyr K, Hjellvik V, Skurtveit S, Furu K. Trends in prescription drug use during pregnancy and postpartum in Norway, 2005 to 2015.Pharmacoepidemiology and drug safety. Sep 2018;27(9):995-1004.5. Lutz BH, Miranda VIA, Silveira MPT, et al. Medication Use among Pregnant Women from the 2015 Pelotas (Brazil) Birth Cohort Study. International journal of environmental research and public health. Feb 5 2020;17(3).6. Koren G, Pariente G. Pregnancy- Associated Changes in Pharmacokinetics and their Clinical Implications.Pharmaceutical research. Feb 12 2018;35(3):61.7. Yerby MS, Friel PN, McCormick K, et al. Pharmacokinetics of anticonvulsants in pregnancy: alterations in plasma protein binding. Epilepsy research. Apr 1990;5(3):223-228.8. Prevost RR, Akl SA, Whybrew WD, Sibai BM. Oral nifedipine pharmacokinetics in pregnancy-induced hypertension. Pharmacotherapy. 1992;12(3):174-177.9. Philipson A. Pharmacokinetics of ampicillin during pregnancy. J Infect Dis. Sep 1977;136(3):370-376.10. Blackburn S. Chapter 9. Cardiovascular System. Maternal, Fetal, & Neonatal Physiology . 5th ed. London, United Kingdom: Elsevier; 2018:251-259.11. Huybrechts KF, Bateman BT, Hernandez-Diaz S. Use of real-world evidence from healthcare utilization data to evaluate drug safety during pregnancy.Pharmacoepidemiology and drug safety. Jul 2019;28(7):906-922.12. Alexander EK, Pearce EN, Brent GA, et al. 2017 Guidelines of the American Thyroid Association for the Diagnosis and Management of Thyroid Disease During Pregnancy and the Postpartum. Thyroid. Mar 2017;27(3):315-389.13. Wesseloo R, Wierdsma AI, van Kamp IL, et al. Lithium dosing strategies during pregnancy and the postpartum period. The British journal of psychiatry : the journal of mental science. Jul 2017;211(1):31-36.14. Betcher HK, George AL, Jr. Pharmacogenomics in pregnancy. Seminars in perinatology. Jan 25 2020:151222.15. Milosheska D, Lorber B, Vovk T, Kastelic M, Dolzan V, Grabnar I. Pharmacokinetics of lamotrigine and its metabolite N-2-glucuronide: Influence of polymorphism of UDP-glucuronosyltransferases and drug transporters. British journal of clinical pharmacology. Aug 2016;82(2):399-411.16. Rogers RC, Sibai BM, Whybrew WD. Labetalol pharmacokinetics in pregnancy-induced hypertension.American journal of obstetrics and gynecology. Feb 1990;162(2):362-366.17. Bates SM, Rajasekhar A, Middeldorp S, et al. American Society of Hematology 2018 guidelines for management of venous thromboembolism: venous thromboembolism in the context of pregnancy. Blood advances. Nov 27 2018;2(22):3317-3359.18. Patel JP, Green B, Patel RK, Marsh MS, Davies JG, Arya R. Population pharmacokinetics of enoxaparin during the antenatal period. Circulation. Sep 24 2013;128(13):1462-1469.19. Garg L, Garg J, Krishnamoorthy P, et al. Influence of Pregnancy in Patients With Congenital Long QT Syndrome. Cardiology in review. Jul/Aug 2017;25(4):197-201.20. Clunies-Ross N, Roston TM, Taylor J, et al. The Effect of Carbetocin Dose on Transmural Dispersion of Myocardial Repolarization in Healthy Parturients Scheduled for Elective Cesarean Delivery Under Spinal Anesthesia: A Prospective, Randomized Clinical Trial. Anesthesia and analgesia. Mar 5 2020.21. Liou SC, Chen C, Wong SY, Wong KM. Ventricular tachycardia after oxytocin injection in patients with prolonged Q-T interval syndrome–report of two cases. Acta anaesthesiologica Sinica. Mar 1998;36(1):49-52.22. Wilmer E, Chai S, Kroumpouzos G. Drug safety: Pregnancy rating classifications and controversies.Clinics in dermatology. May-Jun 2016;34(3):401-409.23. Barr M, Jr., Cohen MM, Jr. ACE inhibitor fetopathy and hypocalvaria: the kidney-skull connection.Teratology. Nov 1991;44(5):485-495.24. Carmichael SL, Shaw GM. Maternal corticosteroid use and risk of selected congenital anomalies.American journal of medical genetics. Sep 17 1999;86(3):242-244.25. Czeizel AE, Rockenbauer M. 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In a recent issue of Br J Clin Pharmacol Smith et al1 published an outstanding commentary titled ‘Dosing will be a key success factor in repurposing antivirals for Covid-19’. They highlighted that the success in our repurposing efforts will be dependent on ‘getting the dose right’ for drugs which have been developed for different indications and stressed some of the unique challenges of treating this particular disease. They pointed the reader to lopinavir/ritonavir (LPV/r) as an example of a repurposed antiviral and the limited experience of this drug regimen (and other treatments) in the elderly population with comorbidities – ie those most at risk from Covid-19. It is on the issue of comorbidities, polypharmacy and drug-drug interactions (DDIs) that we wish to comment.

Drug disposition in children is impacted by developmental changes in drug absorption, distribution, metabolism and excretion. This mandates the need for dosing regimens specifically tailored to children. Yet, there are gaps in the knowledge on these developmental changes, for example regarding hepatic and renal drug transport and drug metabolism, putting children at risk for subtherapeutic or toxic drug exposure. Pediatric drug research is faced with ethical and analytical challenges. This review addresses how these knowledge gaps can be filled and challenges can be overcome by using innovative study designs.