In the context of the current COVID-19 pandemic, what are the lessons clinical pharmacology could learn to improve our teaching practice and involvement in research and ethics committees to make sure we are better prepared for the next emergency. Is there something in the light of the hydroxychloroquine hype that we as clinical pharmacologists or our professional societies could have done better? We propose updating the way we teach about drug development, rules and ethics of off-label prescribing and critical appraisal of primary sources when guidelines and top-level evidence are not available. Clinical pharmacology should play a leading role in the future re-definition of processes and guidelines for emergencies such as the one we faced in 2020.

Dear editor,Given time, drug discovery programmes will undoubtedly yield highly potent drugs to form the basis of optimised COVID-19 regimens. However, if efficacious therapies can be identified from current medicines, repurposing represents the fastest route to establish deployable interventions and buy time for vaccine and novel drug development. It is important to note that effective medicines were rigorously optimised for the treatment of specific indications. Route of administration, dosage and schedules for existing therapies were optimised to provide adequate plasma/tissue pharmacokinetics and safety for their target disease or condition. These cannot be assumed to be optimal for COVID-19 but are often highly predictable from pre-existing data and clinical experience. For example, hydroxychloroquine and lopinavir/ritonavir recently failed to deliver benefits in RCTs for mild/moderate and severe disease,1, 2 but the clear disconnect between reportedin vitro antiviral activity and known human pharmacokinetics after administration of approved doses was predictable.3Interpretation of laboratory-based antiviral activity assessments is complicated by current uncertainty regarding the appropriateness of the existing model systems. The majority of in vitro antiviral screening assays have utilised Vero cells, which were derived from the kidney of African Green Monkey in the 1970s, and the lack of clinical evidence for which to validate the exposure-response relationship in humans is problematic. Evidence is emerging that the anti-SARS-CoV-2 activity of drugs may be higher in cells derived from humans. However, the question of which cell types are most representative of in vivo performance is yet to be addressed, and all that can really be concluded from current knowledge is that the susceptibility of SARS-CoV-2 to antivirals is cell-type-dependent. The consequences of this in terms of the variety of cell types known to be infected and/or sustain productive infection in vivo is equally uncertain, and further exacerbated by the lack of robustly validated animal models. However, repurposed drugs cannot be assumed to be active against SARS-CoV-2 at a dose that was optimised on the basis of potency for and accumulation at their initial therapeutic target.Nucleoside/nucleotide polymerase inhibitors have proven highly successful for other viruses, but usually require combination with another drug class. Remdesivir and favipiravir have in vitro anti-SARS-CoV-2 activity across multiple studies, and the unprecedented speed at which they have transitioned through COVID-19 RCTs can only be commended.4, 5, 6 Daily IV infusion may make inherent sense for severely ill patients, but a transformational impact for COVID-19 can only be realised if wide compatibility with global healthcare systems and equitable access across all country contexts is achieved. While reduction in symptom duration may mitigate healthcare saturation in high-income countries, the absence of a clear benefit for mortality diminishes game-changing potential. However, the clinical validation of the antiviral activity of such drugs will make them clear candidates for implementation as part of community-based interventions if other challenges are addressed. Importantly, the combination of nucleoside analogues with a secondary target such as the protease has stood the test of time in antiviral pharmacology. The recent reports of low-dose dexamethasone leading to an impact on mortality7 is a significant step forward but long-term mitigation of viral transmission, with subsequent economic and social restrictions, requires antiviral treatment or prevention to minimise hospitalisation through a community-targeted approach.Focussing on existing single drugs, and not appropriately formulated medicines, will require the rethinking of a number of medicine development parameters such as posology, reformulation and therapeutic index (Figure 1); current HIV medicines, for example, are formulated for chronic (life-long) dosing to moderate and control disease but a successful COVID-19 therapy will likely require only a short term acute administration to rapidly cure the patient. Conversely, different considerations are required for longer-term applications in COVID-19 chemoprophylaxis, which could have a dramatic effect on control of the pandemic.Many advanced drug delivery technologies have emerged in recent years. Long-acting drug delivery involving injectable, implantable or microarray patch mediated delivery have attracted enormous recent interest for prevention of other infectious diseases,8, 9 and the ability to deliver potent antiviral combinations for a period of months could play a transformational role in the absence of a safe and efficacious vaccine. The physicochemistry and activity of the polymerase inhibitors, and other drugs with known anti SARS-Cov-2 activity, also warrants investigation of pulmonary delivery via nebuliser or metered dose inhaler for direct dosing to the upper airways to supplement systemic drug delivery as pre- or post-exposure prophylaxis. Several advanced drug delivery strategies can be applied rapidly and do not need to be prohibitively expensive for global community programmes. It seems unlikely that a global pandemic can be ended if effective medicines are only available to the few and equitable access is therefore of benefit to all. Importantly, relying solely upon pre-existing formulations and posologies optimised for other diseases carries inherent risk of rejecting drug candidates with an otherwise high potential for global impact.

Aim This study aimed to examine trends in prescribing of anti-dementia drugs in primary care in England between 2009-2019 and to investigate the impact of deprivation, regional demography and disease prevalence on prescribing practices. Methods Analysis of publicly available government data from various sources pertaining to primary care prescribing and demographics was conducted. All primary care prescription data pertaining to anti-dementia drugs and antipsychotic drugs in England between 2009-2019 were extracted and adjusted for inflation and populations changes. Data across English Clinical Commissioning regions and groups were compared to explore the association between prescribing trend, deprivation, regional demography and dementia prevalence. Anti-psychotic drugs prescribing trends were used as reference comparators. Results The number of prescription items for anti-dementia drugs in England increased by approximately three-folds from 24 items/1,000 populations in 2009 to 70.9 items/1,000 populations in 2019; prescribing of antipsychotics increased by 37.6%. In 2019, the least deprived areas had approximately twice the rate of prescribing of anti-dementia drugs compared to the most deprived areas [median (IQR) values of 46.7 (36.6-64.8) vs 91.23 (76.2-95.1) items/1,000 populations respectively]. A weak positive correlation (Pearson’s correlation-coefficient 0.371, p=0.413) was observed between dementia prevalence and prescribing rates. Conclusions The three-fold rise in the number of prescription items for anti-dementia drugs in the study period reflects the policy emphasis on early diagnosis and treatment of dementia. Higher rates of prescribing in the least deprived areas may be reflective of higher life expectancy, better diagnoses and access to treatments. Such differences need to be investigated further.

Abstract Prescription medicine misuse, especially misuse of opioids has become a major public healthcare issue in many developed countries such as the United States of America and Australia where this is associated with significant morbidity (Emergency Department visits due to acute toxicity) and mortality. In this review, we looked at the available data obtained from peer-reviewed articles and population surveys to gain an insight into the current situation in the Asia Pacific region. There is currently limited information available, but data from subpopulation surveys in a number of countries suggests that prescription medicine misuse is likely to be an issue of concern from a public health perspective in the Asia Pacific region. The available data suggest that misuse prevalence rates and the medicines that are commonly misused are similar to countries such as the USA and United Kingdom. Further studies are required to determine the overall prevalence of misuse, the harms associated with this and the sources of drugs being misused so that appropriate interventions can be implemented to tackle issues related to prescription medicine misuse in this region. Keywords: Prescription medicine misuse, drug abuse, opioids, benzodiazepines, GABA analogues

Aim. The multi-part Unified Parkinson’s Disease Rating Scale is the standard instrument in clinical trials. A sum of scores for all items in one or more parts of the instrument is usually analyzed. Without accounting for relative importance of individual items, this sum of scores conceivably does not optimize the power of the instrument. The aim was to compare the ability to detect drug effect in slowing down motor function deterioration, as measured by Part III of the Scale - motor examinations - between the item scores and the sum of scores. Methods. We used data from 423 patients in a Parkinson’s disease progression trial to estimate the symptom severity by item response modelling; modelled symptom progression using the severity and the sum of scores; and conducted simulations to compare the sensitivity of detecting a broad range of hypothetical drug effects on progression using the severity and the sum of scores. Results. The severity endpoint was far more sensitive than the sum of scores for detecting treatment effects, e.g., requiring 280 versus 570 patients per arm to achieve 60% Probability of Success for detecting a range of potential effects in a 2-year trial. Items related to the left side of the body were most informative; and the domain relevance of tremor items was questionable. Conclusion. This analysis generated clear evidence that longitudinal modelling of item scores can enhance trial efficiency and success. It also prompted the needs for a consensus on the placement of the tremor items in the instrument.

Aims: The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing sub-groups of populations to potentially higher drug exposure levels? The aim of this study was to build an extensive knowledge-base of the effect of intrinsic and extrinsic factors on the disposition of several repurposed COVID-19 drugs. Methods: Verified physiologically‐based pharmacokinetic (PBPK) models were used study the effect of COVID-19 drugs PK in geriatric patients, race, organ impairment, DDI risks, disease-drug interaction for repurposed COVID-19 drugs. Furthermore, these models were used to predict epithelial lining fluid (ELF) exposure which is relevant for COVID-19 patients by accounting for the interplay between cytokines and metabolic disposition. Results: The simulated PK profiles suggest no dose adjustments are required based on age and race for COVID-19 drugs; however, sometimes dose adjustments are warranted for patients exhibiting hepatic/renal impairment in addition to COVID-19 co-morbidity. PBPK model simulations suggest ELF exposure to attain a target concentration was adequate for most drugs except azithromycin, atazanavir and lopinavir/ritonavir. Conclusion: We demonstrate that systematically collated data on the ADME, human PK parameters, DDIs, and organ impairment has enabled verification of simulated plasma and lung tissue exposure of many repurposed COVID-19 drugs to justify broader recruitment criteria for patients. In addition, developed PBPK model helped to assess the correlation between target site exposure to relevant potency values from in vitro studies for SARS-CoV-2.

A commentary on: Personalised dosing of vancomycin: a prospective and retrospective comparative quasi-experimental study by Luqman Vali et al.Vancomycin is frequently used to treat Staphylococcal infections resistant to beta-lactam antibiotics. Overexposure to vancomycin increases risk of nephrotoxicity while underexposure can lead to therapeutic failure. This narrow therapeutic window makes it necessary to measure vancomycin serum concentrations aiming for an effective and justifiable dose. Often mathematical software is used to calculate a pharmacokinetic (PK) / pharmacodynamic (PD) target and predict the right vancomycin dosage.In this journal, Vali et al. compared the prospective results of a bedside Bayesian-guided software package (DoseMeRx) to guide vancomycin dosing with retrospective results of vancomycin-dosing with a standard algorithmic approach. Bedside Bayesian-guided dosing resulted in significantly more area under the curves (AUC) measured within the target range (350 – 450 mg/L*h) and in a significantly higher percentage of time in the acceptable range in comparison with the standard algorithmic approach.Unfortunately, the authors were not able to relate their findings to clinical outcomes such as clinical cure or mortality, possibly due to insufficient power. Still, PK/PD modelling is the cornerstone in calculating vancomycin dosages and user friendly bedside software can increase the availability and integration of these models in clinical practice. However, the precision of the dose calculations based on pharmacokinetic and pharmacodynamic modelling can be misleading and should not be used to determine the optimal dose without further considerations.Several factors impact the interpretation of individual dose calculations of antibiotics based on PK/PD modelling: the PK/PD-index of the antibiotic that is used to predict the efficacy; clinical and pharmacological factors that influence PK and the accuracy of minimal inhibitory concentration (MIC) of the causative pathogen. We will discuss these three factors and elaborate on their influence on dose calculations.Several studies aimed to establish the dose-response relation of vancomycin. Generally accepted vancomycin PK/PD targets are an AUC/MIC > 400 or a trough serum or plasma level (Ctrough)/MIC > 10-15. Using the AUC/MIC as predicting parameter requires the use of specialized software to calculate the AUC on intermittent dosing regimens, but is generally accepted as the most appropriate PK/PD-index of vancomycin. A recent meta-analysis of several cohort studies showed that AUC/MIC guided dosing resulted in a lower incidence acute kidney injury (AKI) in comparison to trough level dosing with an odds ratio of 0.68 (95% CI: 0.46 – 0.99). However, included studies were small, mostly retrospective and the effect of PK/PD-based dosing on AKI and other clinical outcomes therefore need to be confirmed in larger studies.Experiments with novel in-vitro models, such as two-compartment hollow fiber models, could add valuable information to the currently available evidence on the optimal PK/PD index of vancomycin. However, as far as we are aware, studies with these novel in-vitro models with vancomycin have not yet been reported.Tissue penetration is another major determinant in applying PK/PD calculations in clinical practice. The extent of tissue penetration depends on the solubility of the compound in fat (or octanol - thelog P ), the acid dissociation constant (pKa), the extent of protein binding, the molecular mass and the affinity to certain transmembrane transporters, such as P-glycoprotein. It could be questionable if serum or plasma concentrations are a representative factor in the treatment outcome when the tissue penetration of an antibiotic is low, while the infection is mainly situated in tissue. A good example is the high molecular mass of vancomycin and therefore low penetration characteristics.Microdialysis, has delivered promising results to quantify the tissue penetration of antibiotics. With microdialysis, a small dialysis tube is placed in the tissue of interest. Due to diffusion of the antibiotic from the extracellular fluid into the dialysis fluid, the antibiotic concentration can be measured in the dialysate. Microdialysis can help to extrapolate the PK/PD index to infections in tissue either by computing serum-tissue ratios or by building multiple-compartment PK models. However, a complicating aspect is the large interindividual variation in tissue concentrations. Studies on microdialysis with vancomycin have shown large variation in interstitial fluid concentrations which could not be explained by patient characteristics. In addition, the penetration of vancomycin in the central nervous system (CNS) is also highly variable. For CNS infections, one should consider to administer vancomycin intrathecally or switch to a different antibiotic with proven acceptable penetration in the CNS, such as linezolid. Overall, vancomycin tissue penetration is relatively low but some high unexplained variability is observed. Overall, microdialysis and hollow fiber models are potentially useful techniques in gaining more insight in the relation between serum concentrations, tissue concentrations and efficacy. Yet, clinical evidence for their use is still limited.Beside the optimal PK/PD target and extent of tissue penetration, the way of dosing is also of importance. Continuous vancomycin administration is increasing in clinical practice, making sampling easy as the concentration measured does not depend on the time of sampling. Furthermore calculation of the AUC0-24h (mg/L*h) of vancomycin on continuous infusion is simple: multiply the measured concentration (in mg/L) by 24. In a meta-analysis the incidence of nephrotoxicity was found lower in patients treated with continuous vancomycin vs. patients treated with intermittent vancomycin, with no difference in treatment failure or mortality. A limiting practical factor in applying continuous vancomycin is the availability of one dedicated intravenous (IV) catheter or lumen, since vancomycin is incompatible with many other medicines and IV fluids. In the paper by Vali et al. we missed vancomycin continuous infusion simulations to collect evidence for this upcoming method of administration.A final major determinant of PK/PD modelling is the MIC. The MIC is defined as the lowest concentration that inhibits growth of the isolated micro-organism. The golden standard for MIC testing is broth microdilution. However, many clinical microbiological laboratories use automated systems or antimicrobial gradient strips for their first-line antimicrobial susceptibility testing (AST). These methods are rarely precise enough to be used to calculate the AUC/MIC or Ctrough/MIC. Therefore, Mouton et al. suggested to include the epidemiological cut-off value (ECOFF) when interpreting MIC results for target attainment calculations. The ECOFF is determined as the highest MIC of the bacterial species of interest without acquired resistance, i.e. the wildtype population. Using the ECOFF instead of the MIC, however could add potential risks of overdosing of an antibiotic for the wildtype population of a micro-organism with broad MIC ranges. For example, the suggested ECOFF of S. aureus for vancomycin is 2 mg/L, which would indicate that the target AUC0-24hshould be above 800 mg/L*h (AUC/MIC > 400). Such high AUCs increase the risk of nephrotoxicity and should not be applied in regular care. PK/PD-based modelling with accurate MIC testing therefore seems of importance to decrease risk of overdosing.In conclusion, the use of software programs can facilitate the measurement of these targets and the prediction of the right dose of vancomycin. The prescriber and pharmacist should, however, always be aware of the ’pseudo- precision’ of those calculations: many other factors influence the efficacy and toxicity of vancomycin besides the trough concentration or the AUC.

Understanding of the term ‘Precision Medicine’ is variable. For clinicians, pharmacists and clinical pharmacologists, it refers to the right decision (treat or not), right drug, right combination, right timing and right dose, taking into account the clinical trial data for the patient group being treated, and finessing that to the individual biological and pharmacological variables either evident, or likely to be evident based on knowledge about comorbidity and body size.To scientists, precision medicine can mean either developing a new molecule to fit a specific target or cell of interest, or ‘finding’ based on mathematical and chemical profiling existing drugs that might ‘fit’ the target of interest (1). However, this focus on ‘targets’ as the method to improve precision has seemingly ignored the well-known principles of radiobiology, cancer biology and pharmacology, and has not delivered the improved health outcomes expected (2). Similarly, since 2015, U.S. and other government’s multi-billion-dollar investments into ‘precision’ drugs “delivering the right treatments, at the right time, every time to the right person whilst helpful to understand some aspects of disease pathophysiology, has also fueled this single target focus (3).In this Themed issue discussion on aspects of science and medicine people refer to as precision medicine approach are covered. Although varied, much discussion is related to the importance of understanding the way each individual both handles and responds to a drug, and specific dose. How to implement individualized dosing into practice however can be an even more challenging area, with different levels of precision costing different amounts, with a spectrum of clinical and economic benefits.Added to this difficulty is the systematizing of regimen and dose for specific cancers which have come into oncology practice over the last few years. Moynihan et al argue that the financial dependence of research on industry funding creates a “sponsorship bias” that overplays efficacy and underplays toxicity. This was confirmed in a systematic review comparing industry sponsored with independently funded trials (4).This is not just an issue with interpretation of results but goes back to trial design. The choice of a comparator may make the outcome of the study drug more favorable (4). Over the years in cancer trials, there has certainly been a move from the principle of treating until maximum response and then allowing a patient time without symptoms or side effects of treatment to studies which are designed to continue treatment until relapse or unacceptable toxicity. This maximizes drug use but is there evidence that prolonging use of a drug maximizes outcomes?Maintenance strategies in metastatic disease can be simply continuing the drug used in induction or switching to another drug, which really can be considered as early second line treatment (5). Although established in lymphomas, randomized studies of continuous maintenance therapy in non-small cell lung cancer (NSCLC) led to no improvement in response or survival and similarly for survival in colorectal cancer (5,6). Prolonging first line therapy in breast cancer only showed a marginal survival benefit. There are ongoing studies, but prolonging induction therapy lacks the evidence for widespread adoption. Switching to another drug or targeted therapy, as an early second line treatment, has shown prolonged survival over induction alone in several tumour types (5).The duration of targeted therapies provides examples of how trial design influences practice. The initial studies of trastuzumab in adjuvant breast cancer initially reported at the American Society of Clinical Oncology in 2005 were designed to give 12 months of therapy and that became the standard of care (7). An ongoing study at the time was comparing 12 months with 24 months. (8). However, an independent French group looked at 6 months compared to 12 months and it is only in 2019 that the final analysis could not show non-inferiority of 6 months of treatment (9). Meanwhile the FinHER study in Finland showed the efficacy and cost-effectiveness of only 9 weeks of adjuvant trastuzumab after chemotherapy (10, 11).In terms of the dose given, the current common method of dosing cytotoxic drugs is based on a patient’s body surface area (BSA). This can be inaccurate with considerable variation between patients because patient-related factors such as organ function, age, gender, activity of metabolizing enzymes, drug resistance and concomitant drugs can influence the pharmacokinetics and pharmacodynamics (12). This gives rise to pharmacologically-based dosing being explored to make individual patient dosing more precise.The first step, however, in the treatment of cancer is to select the drug or drugs most likely to be effective. In the era of precision medicine what is being investigated is identifying mutations in genes or changes in the expression of genes or proteins specific to a tumour, which can be targeted by therapeutics (13). Detecting multiple genomic changes has been made possible by technological advances like next generation sequencing (NGS) replacing older single gene testing. Use multiple platforms combining sequencing of DNA with RNA sequencing and with the more established techniques such as immunohistochemistry (IHC) maximizes the potential to discover druggable targets (14). IHC detects changes at the protein level that reflect gene amplifications such as HER-2 in breast cancer, gastric and colorectal cancer which can be targeted with trastuzumab. Rearrangements include EML4-ALK translocation in non-small cell lung cancer which can be targeted by drugs such as crizotinib. Now there is testing for biomarkers related to PD-L1 expression in various tumours which can be targeted by checkpoint inhibitors such as atezolizumab.Molecular profiling which allows matching treatments for cancers to their targets has resulted in a boost for new drug development in rare cancers by using drugs targeted to molecular biomarkers that they have in common with more common cancers, in basket trials (15).Limitations of gene expression profiling and IHC can be illustrated in diffuse large B-cell lymphoma (DLBCL) as summarized by Ofori et al in this issue of the Journal (16). Its subtypes defined by the cell of origin can predict survival and response to chemotherapy, and were initially classified by gene expression profiling. However, fresh tissue had to be available and often only major centers had the capability. IHC methods were subject to observer error. The other issue was that serial tumour profiling during treatment may be able to detect emerging resistance but serial biopsies may not be feasible and surveillance post treatment was only available by imaging, which has not been shown to be associated with a survival benefit.Liquid biopsies have the potential for solving these issues. Biomarkers in blood or other body fluids can be identified, including from circulating tumour DNA (ctDNA), circulating tumour cells (CTC) or exosomes. Circulating tumour DNA fragments are shed from tumour cells and show mutations and methylation profiles of the tumour which could be used to identify targets or predict recurrence in tumours such as DLBCL (17).Circulating tumour cells are derived from primary tumours or their metastases and either actively or passively enter the circulation. Their DNA, RNA and proteins could be used to discover the molecular profile of the tumour and their numbers can correlate with treatment outcome (16). De Souza et al have identified technological and interpretive challenges to overcome before CTCs are used routinely in the clinic (18).Exosomes, formed when a cell membrane buds off with contents including protein, nucleic acids, sugars and lipids are taken up by other cells and represent communication between cells. They can circulate in many body fluids. The potential advantage of exomes is their abundance in the fluids and their contents that may reveal multiple biomarkers which in a disease such as DLBCL could be used to subtype and therefore predict prognosis, be used as surveillance during therapy and reveal resistance mechanisms. They could then be used to follow-up post treatment (16).A further tool to guide dosing of anti-cancer drugs and predicting toxicity and response prior to their administration is pharmacogenomics reviewed by Carr et al (19). Examples with the strongest evidence are assaying for dihydropyrimidine dehydrogenase (DPYD) which is the rate limiting enzyme for 5-FU metabolism, encoded by a gene with multiple variants. Identifying the variant alleles of thiopurine methyltransferase (TMPT) can identify a low activity genotype which metabolizes 6-mercaptopurine to an inactive mercaptopurine resulting in less metabolism of 6-MP to toxic thioguanine nucleotide metabolites. There are many other potential applications of pharmacogenomics, but with equivocal or less evidence. The more widespread use of NGS will allow easier identification of rarer mutations associated with adverse drug reactions. The lack of routine use of pharmacogenomics is multifactorial including the expense, accessibility, the time for processing and the complex interactions including between genomics, clinical factors and the microbiome which account for the individual variations (19).Personalised drug dosing is important in oncology to prevent overdosing, which otherwise may only become evident when a patient develops severe side effects, or underdosing resulting in lack of efficacy, which may not be revealed until scans show a lack of tumour response . The evidence for some drugs that drug exposure is related to efficacy and toxicity allows for therapeutic dose monitoring (TDM) such as is used for dosing antimicrobials. Some examples of attempting TDM with cytotoxics illustrate the challenges.For intravenous 5-FU while DPYD genotyping is useful, more precision is needed for bolus and infusional regimens in a variety of cancers, including head and neck and colorectal cancer. In articulating the importance of TDM dosing Schneider JJ et al. in this themed issue, reiterate that 5-FU dosing by BSA only results in 20-30% patients achieving the therapeutic range. Exploring the relationship between 5-FU area under the curve (AUC) and a target dose resulted in the recommendation of a therapeutic exposure range of 20-30mgh/L for 46-hour infusion schedules (20). Unfortunately, data is lacking to apply TDM dosing to the oral prodrug capecitabine, which is just as effective as 5-FU but better tolerated.Other common cytotoxic drugs are more problematic. Muth et al reviewed the taxanes; paclitaxel, docetaxel, nab-paclitaxel and cabazitaxel which illustrate some of the complexities of TDM dosing (21). Paclitaxel which is commonly dosed weekly or 3 weekly has non-linear pharmacokinetics, undergoes hepatic metabolism and biliary excretion and there are interactions with its solvent cremophor, however the time above a plasma concentration of 0.05 µmol/L does predict neutropenia and polyneuropathy and may be associated with a favourable clinical outcome, making TDM dosing desirable. Docetaxel, is also extensively metabolised in the liver, has linear kinetics, but is formulated with polysorbate 80 rather than cremophor. Weekly docetaxel has a more favourable toxicity profile that 3-weekly dosing but it is AUC that predicts febrile neutropenia, mucositis and diarrhoea. Less research has been done than with paclitaxel but a small randomized study of TDM and target concentration intervention (TCI) compared to BSA didn’t show a clear advantage for TDM and TCI for docetaxel (22). Unfortunately, is no prospective TDM data for carbazitaxel or nab-paclitaxel.Early in the development of carboplatin the relationship between drug exposure and efficacy and toxicity was established and dosing was more accurately based on renal function (glomerular filtration rate- GFR) than BSA. However, for specific groups such as infants, anephric patients and those receiving high-dose carboplatin, TDM dosing is more desirable that dosing based on (GFR) as summarized by Barnett S et al (23).For TDM to be translated into clinical practice, the evidence base must expand, and sampling strategies need to be simplified, perhaps by micro sampling such as using dried blood spots or using body fluids other than blood. There must be better access to TDM laboratories, and the provision of clinical decision support for interpreting the results of pharmacometrics which use Bayesian estimations to combine pharmacokinetics, individual patient characteristics and drug concentrations (24).Finally, a barrier which must be addressed to allow clinical translation of TDM is the demonstration of its economic efficacy which Vithanachchi DT et al present in a descriptive review (25). They reviewed 11 studies and noted that only a few drugs have been studied. However, all studies reviewed found TDM to be cost effective, based on established incremental cost-effectiveness ratios. In future newer therapeutics should have an economic analysis of TDM, incorporating the associated clinical evidence, which in the short term is reduced toxicity and the long term, a survival advantage.REFERENCES1. Martin JH, Bowden NA. Drug Repurposing – Overcoming the translational hurdles to clinical use. Pharmacol Res Perspect 2019, Nov 26, https://doi.org/10.1002/prp2.548.2. Fay M, Head R, Martin J. Where is the radiobiology and pharmacology research to improve outcomes on glioblastoma? J Neurooncol 2015, 124: 1-3.3. Obama B. The Precision Medicine Inititive https://obamawhitehouse.archives.gov/precision-medicine [Last Accessed 11 Dec 2020]4. Moynihan R, Beros L, Hill S et al. Pathways to independence: towards producing and using trustworthy evidence. BMJ 2019, Dec 3; 367:16576. Doi: 10.1136/bmj.e3502.5. Rowinski E, Fournel P, Bernichon E, Bouleftour W, Magné N, Mery B. Maintenance therapy in metastatic solid tumours. Innovative strategy or simply second-line treatment? Am J Clin Oncol 2019, 42: 615-623.6. von Plessen C, Bergman B, Anderson O et al. Palliative chemotherapy beyond three courses conveys no survival or consistent quality-of-life benefits in advanced non-small-cell lung cancer.Br J Cancer 2006, 95: 966-9737. Perez EA, Romond EH, Suman VJ et al. 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Short-course adjuvant trastuzumab therapy in early stage breast cancer in Finland: cost-effectiveness and value of information analysis based on the 5-year follow-up results of the FinHer trial. Ann Oncol 2011, 50: 344-352.12. Kaestner SA, Sewell GJ. Chemotherapy dosing part I: scientific basis for current practice and use of body surface are. Clin Oncol (R Coll Radiol) 2007, 19: 23-37.13. Malone ER, Oliva M, Sabatini PJB, Stockley TL, Siu LL. Molecular profiling for precision cancer therapies. Genome Med 2020 12:8 https://doi.org/10.1186/s13073-019-0703-1. [Last accessed Jun 10 2020].14. Zimmer K, Kochner F, Spizzo G, Salem M, Gastl G, Seeber A. Treatment according to molecular profiling in relapsed/refractory cancer patients: a review focusing on latest profiling studies. Comput Struct Biotechnol J 2019, 17: 447-453.15. Wang S, Chen R, Tang Y et al. Comprehensive genomic profiling of rare tumour: routes to targeted therapies. 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Overcoming barriers to implementing precision dosing with 5-Fluorouracil and capecitabine. Br J Clin Pharmacol 2020, X:XX-XX.21 Muth M, Ojara FW, Joerger M. Role of TDM-based dose adjustments for major taxane anticancer drugs. Br J Clin Pharmacol 2020, X: XX-XX.22. Engel FK, Loos WJ, van der Bol JM et al. Therapeutic drug monitoring for the individualization of docetaxel dosing: a randomised pharmacokinetic study. Clin Cancer Res 2011, 17: 353-362.23 Barnett S, Kong J, Makin G, Veal GJ. Over a decade of experience with carboplatin therapeutic drug monitoring in a childhood cancer setting in the United Kingdom. Br J Clin Pharmacol 2020, X: XX-XX.24 Menz BD,, Stocker SL, Verougstraete N et al. Barriers and opportunities for the clinical implementation of therapeutic drug monitoring in oncology. Br J Clin Pharmacol 2020, X: XX-XX.25. Vithanachchi D, Maujean A, Downes MJ, Scuffham P. 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Clinicians, patients, administrators and researchers have become increasingly frustrated by the lack of indication (i.e. problem) information included in prescriptions, despite the obvious benefit this would provide to patients and other healthcare providers [1]. Medication indications are not routinely documented by prescribers, both in inpatient and outpatient settings.[2, 3] Calls have been made to introduce a sixth ‘right’ into the medication management process, whereby the right patient is given the right drug and dose at the right time via the right route for the right indication [4]. Indications-based prescribing has recently gained traction as a potential way forward to facilitate indication documentation [4, 5]. Indications-based prescribing, not currently supported by most electronic prescribing systems (EPSs), describes the scenario where prescribers initially select an indication, not a medication, and the EPS presents the user with suggested medications for addressing the problem. There are clear advantages with this approach, including those associated with guided prescribing (e.g. more appropriate drug selections) and with indication documentation (e.g. improved communication between providers), prompting work to begin on developing EPS functionality in the US to support indications-based prescribing. In a recent usability evaluation of a prototype of this functionality, indications-based prescribing was more efficient to use, resulted in fewer medication errors and in higher usability scores than the traditional EPS functionality [6].

Gene therapy medicinal products have the potential to provide curative treatment to many diseases with current limited therapeutic options. As advanced therapy medicinal products (ATMPs), these therapies undergo a centralised, single European Union authorisation by the European Medicines Agency, but the risks, and potential harm to the environment and population at large are weighted in each application, and different interpretations at national level exist. A streamlined procedure is now in place to facilitate a consistent approach for the assessment of the environmental risks of medicines containing genetically modified organisms. This article provides an overview of basic requirements across the EU, an overview of the new streamlined process and discusses available guidance for developers. All these initiatives are aimed to remove hurdles for ATMP developers and facilitate faster access to patients.

Aims In light of the recent safety concerns relating to NSAID use in COVID-19, we sought to evaluate cardiovascular and respiratory complications in patients taking NSAIDs during acute lower respiratory tract infections. Methods We carried out a systematic review and meta-analysis of randomised controlled trials and observational studies. Studies of adult patients with short-term NSAID use during acute lower respiratory tract infections, including bacterial and viral infections, were included. Primary outcome was all-cause mortality. Secondary outcomes were cardiovascular, renal and respiratory complications. Results In total, eight studies including two randomised controlled trials, three retrospective and three prospective observational studies enrolling 44140 patients were included. Five of the studies were in patients with pneumonia, two in patients with Influenza, and one in patients with acute bronchitis. There was uncertainty as to the effects on mortality (RR 0.87 [0.63, 1.18]), but pleuro-pulmonary complications were more common with NSAID use (RR 2.62 [1.96, 3.50]). However, all studies exhibited high risks of bias, primarily due to lack of adjustment for confounding variables. Cardiovascular outcomes were not reported by any of the included studies. Conclusion Short-term NSAID use during acute lower respiratory tract infections was associated with more pleuro-pulmonary complications although this may be due to confounding by indication. There remains significant uncertainty on the effects on mortality. Such results should be interpreted cautiously given the very low quality of evidence. Mechanistic and clinical studies addressing the captioned subject are urgently needed, especially in relation to COVID-19.

Background and Purpose: SARS-coV-2 pandemic continues to cause an unprecedented global destabilization. There is an urgent need to develop vaccines or identify molecules to treat severe cases and repurposing of drugs is the best approach at this hour. Thalidomide, despite having an infamous history has been successfully repurposed and tested for various disease conditions including inflammatory diseases and tumor. Few reports emphasize the use of thalidomide with a SARS-coV-2 pneumonia patient being successfully treated with thalidomide. Experimental Approach: A meta-analysis comparing the transcriptomes of SARS-coV-2 infected tissues with thalidomide and lenalidomide-induced transcriptomic changes in transformed lung, endothelial and hematopoietic models was performed. Key Results: Thalidomide and lenalidomide exhibited pleiotropic effects affecting a range of biological processes including inflammation, immune response, angiogenesis, MAPK signaling, NOD-like receptor signaling, TLR signaling, leukocyte differentiation and innate immunity, the processes which are aberrantly regulated in severe COVID-19 patients. In addition, we show the similarities between the expression profiles of SARS-coV-2 infected lung and systemic lupus erythematous. Conclusion and Implications: The present study recommends thalidomide analogs as a “better fit” to treat severe cases of novel viral infections, healing the damaged network by compensating the impairment caused by the Coronavirus disease-2019 (COVID-19).

Aim: Pharmacovigilance data are primarily used to identify adverse drug reactions. However, scanning for associations of drugs and adverse events that occur less frequently than expected provides hypotheses for drug repurposing, i.e. a known drug could be therapeutically beneficial for a new indication like the coronavirus disease (COVID-19). Methods: Drugs associated with viral respiratory tract infections and/or influenza were extracted from the U.S. FAERS pharmacovigilance data using OpenVigil2.1-MedDRA17, filtered for significant inverse associations (punadj<0.05), checked for plausibility, and categorised by their WHO Anatomical Therapeutic Chemical (ATC) classification code. Results: ATC clustering of 82 candidate drugs revealed anti-diabetics, neuropharmacologic sigma-receptor agonists, peptidase inhibitors, kinase inhibitors and anti-androgens. Chloroquine appears as a statistically significant risk factor for viral diseases supporting actual knowledge. Conclusion: OpenVigil 2 delivers new hypotheses for drug repurposing, theoretically for all indications. There is affirmative data for some of our results; the remaining proposed candidate drugs without already known antiviral mechanism of action should stimulate further exploration.

Aim: We hypothesize that the efficacy of COVID-19 therapeutic candidates will be better predicted by understanding their effects at various points on a viral cell cycle, in particular, the specific rate constants, and that drugs acting independently of these specific discrete sites may not yield expected efficacy. We hypothesize that drugs, or combinations of drugs that act at specific multiple sites on the viral life cycle have the highest probability of success in the treatment of early infection phase in COVID-19 patients. Methods: Using a target cell limited model structure that had been used to characterize viral load dynamics from COVID-19 patients, we performed simulations to show that combinations of therapeutics targeting specific rate constants have greater probability of efficacy and supportive rationale for clinical trial evaluation. Results: Based on the known kinetics of the SARS-CoV-2 life cycle, we rank ordered potential targeted approaches involving repurposed, low-potency agents. We suggest that targeting multiple points central to viral replication within infected host cells or release from those cells is a viable strategy for reducing both viral load and host cell infection. In addition, we observed that the time-window opportunity for a therapeutic intervention to effect duration of viral shedding exceeds the effect on sparing epithelial cells from infection or impact on viral load AUC. Furthermore, the impact on reduction on duration of shedding may extend further in patients who exhibit a prolonged shedder phenotype. Conclusions: Our work highlights the use of model-informed tools to better rationalize effective treatments for COVID-19.

Aim: To assess the potential of interleukin-6 (IL-6) signaling blockade in the lung to treat SARS-CoV-2 infection via model-based simulation by exploring soluble IL-6 receptor (sIL-6R) sequestration by tocilizumab (TCZ) and IL-6 sequestration by siltuximab (SIL). Methods: Literature values of IL-6, the IL-6 antagonist SIL, sIL-6R, the IL-6R antagonist TCZ, and their respective binding constants were used to develop a model to predict the impact of treatment on IL-6 signaling. Models were used to generate simulated bronchoalveolar lavage (BAL) concentrations for normal subjects, subjects at risk of developing acute respiratory distress syndrome (ARDS), and subjects with ARDS were simulated under four conditions: without treatment, treatment with TCZ, treatment with SIL, and treatment with TCZ + SIL. Results: With TCZ intervention, IL-6 levels are unaffected and sIL-6R is reduced somewhat below the Normal case. IL-6:sIL-6R complex only slightly decreased relative to the no-intervention case. With SIL intervention, sIL-6R levels are unaffected and IL-6 is greatly reduced below the Normal case. IL-6:sIL-6R complex is greatly decreased relative to the no-intervention case. With TCZ + SIL intervention, IL-6 and sIL-6R levels are reduced below the Normal case and achieve suppression equivalent to monotherapy results for their respective targets. IL-6:sIL-6R complex reduction is predicted to be greater than monotherapy. This reflects sequestration of both components of the complex and the nonlinear binding equilibrium. Conclusion: Co-administration of both IL-6 and IL-6R sequestering products such as SIL and TCZ may be necessary to effectively treat COVID-19 patients who have or are at risk of developing ARDS.

Aim: Although medicine misuse is a public health issue, it has multiple meanings in the medical literature. This study aimed to characterize, classify and identify the most appropriate definitions of medicine misuse. Methods: A systematic review was performed in Medline, ISI Web of Science, SocINDEX, PsycInfo, PsycArticles, and Psychological and Behavioral Sciences Collection, using keywords related to misuse, appropriateness, and medicine between November 1st, 2008 and November 1st, 2018. Additional searches were conducted in websites of regulatory agencies and public health institutions. Two authors independently selected studies providing both definitions and examples of misuse, while a third resolved disagreements. Definitions were used to propose a hierarchical classification based on initiator, intent, purpose, and context of medicine misuse. The study is registered on PROSPERO: CRD42018115789. Results: Of 2,901 identified records, 44 were included. A total of 63 definitions and 60 examples of misuse were retrieved. When the prescriber is initiator and according to intent, potential medicine misuse referred to “intentional or unintentional prescribing not in line with clinical evidence”. Based on context, he could prescribe medicines not clinically justified, i.e. “overprescribing”, or prescribe indicated medicines incorrectly, i.e. “misprescribing”. Among other groups of definitions, those overlapping with drug abuse or medication use errors were considered out-of-scope. Conclusion: This systematic review provides a comprehensive overview of the terms and definitions used to characterize medicine misuse and could serve as a basis for a terminology that makes clear distinctions between misuse, abuse, and errors.

Aims: Thrombocytopoenia is a common major side-effect of cytotoxic cancer therapies. A clinically relevant problem is to predict an individual’s thrombotoxicity in the next planned chemotherapy cycle in order to decide on treatment adaptation. To support this task, two dynamical mathematical models of thrombopoiesis under chemotherapy were proposed, a simple semi-mechanistic model and a comprehensive mechanistic model. In this study, we compare the performance of these models. Methods: We consider close-meshed individual time series data of 135 non-Hodgkin’s lymphoma patients treated with six cycles of CHOP/CHOEP chemotherapies. Individual parameter estimates were derived on the basis of these data considering a varying number of cycles per patient. Parsimony assumptions were applied to optimize parameter identifiability. Models are compared by determining deviations of predicted and observed degrees of thrombocytopoenia in the next cycles. Results: The mechanistic model results in superior fits of individual time series data. Moreover, prediction accuracy of future cycle toxicities by the mechanistic model is higher even if it used data of two cycles, while the semi-mechanistic model used data of five cycles for the corresponding calibrations. Conclusions: We successfully established a quantitative and clinically relevant method for comparing prediction performance of biomathematical models of thrombopoiesis under chemotherapy. We showed that the more comprehensive mechanistic model outperforms the semi-mechanistic model. We aim at implementing the mechanistic model into clinical practice to assess its utility in real life clinical decision making

Background Medication harm has negative clinical and economic consequences, contributing to hospitalisation, morbidity and mortality. The incidence ranges from four to 14%, of which up to 50% of events may be preventable. A predictive model for identifying high-risk inpatients can guide a timely and systematic approach to prioritisation. Aim To develop and internally validate a risk prediction model, for prioritisation of hospitalised patients, at risk of medication harm. Methods A retrospective cohort study was conducted in general medical and geriatric specialties at an Australian hospital, over six months. Medication harm was identified using International Classification of Disease (ICD-10) codes and the hospital’s incident database. Sixty-eight variables, including medications and laboratory results, were extracted from the hospital’s databases. Multivariable logistic regression was used to develop the final risk model. Performance was evaluated using area under the receiver operative characteristic curve (AuROC) and clinical utility was determined using decision curve analysis. Results The study cohort included 1982 patients median age 74 years, of which 136 (7%) experienced ≥1 adverse medication event(s). The model included: length of stay, hospital re-admission within 12 months, venous or arterial thrombosis &/or embolism, ≥ 8 medications, serum sodium < 126 mmol/L, INR > 3, anti-psychotic, antiarrhythmic and immunosuppressant medications, and history of medication allergy. Validation gave an AuROC of 0.70 (95% CI: 0.65-0.74). Decision curve analysis identified that the AIME may be clinically useful to help guide decision making in practice. Conclusion We have developed a risk prediction model with reasonable performance. Future steps include external validation.