Associating adverse drug effects with protein targets by integrating adverse event, in vitro bioactivity, and pharmacokinetic data

Adverse drug effects are unintended and undesirable effects of medicines, causing attrition of molecules in drug development and harm to patients. To anticipate potential adverse effects early, drug candidates are commonly screened for pharmacological activity against a panel of protein targets. However, there is a lack of large-scale, quantitative information on the links between routinely screened proteins and the reporting of adverse events (AEs). This work describes a systematic analysis of associations between AEs observed in humans and bioactivities of drugs while taking into account drug plasma concentrations. In the first chapter, post-marketing drug-AE associations are derived from the United States Food and Drug Administration Adverse Event Reporting System using disproportionality methods, while applying Propensity Score Matching to reduce confounding factors. The resulting drug-AE associations are compared to those from the Side Effect Resource, which are primarily derived from clinical trials. The analysis reveals that the datasets generally share less than 10% of reported AEs for the same drug and have different distributions of AEs across System Organ Classes (SOCs). Using the drugs from the two AE datasets described in the first chapter, the second chapter integrates corresponding bioactivities, i.e. measured potencies and affinities from the ChEMBL database and ligand-based target predictions obtained with the tool PIDGIN, with drug plasma concentrations compiled from literature, such as Cmax. Compared to a constant bioactivity cut-off of 1 uM, using the ratio of the unbound drug plasma concentration over the drug potency, i.e. Cmax/XC50, results in different binary activity calls for protein targets. Whether deriving activity calls in this way results in the selection of targets with greater relevance to human AEs is investigated in the third chapter, which computes relationships between targets and AEs using different measures of statistical association. Using the Cmax/XC50 ratio results in higher Likelihood Ratios and Positive Predictive Values (PPVs) for target-AE associations that were previously reported in the context of secondary pharmacology screening, at the cost of a lower recall, possibly due to the smaller size of the dataset with available plasma concentrations. Furthermore, a large-scale quantitative assessment of bioactivities as indicators of AEs reveals a trade-off between the PPV and how many AE-associated drugs can potentially be detected from in vitro screening, although using combinations of targets can improve the detection rate in ~40% of cases at limited cost to the PPV. The work highlights AEs most strongly related to bioactivities and their SOC distribution. Overall, this thesis contributes to knowledge of the relationships between in vitro bioactivities and empirical evidence of AEs in humans. The results can inform the selection of proteins for secondary pharmacology screening and the development of computational models to predict AEs.Lhasa Limite

Using the theory of planned behavior to predict Texas pharmacists' intention to report serious adverse drug events

textThe purpose of this dissertation was to use the theory of planned behavior (TPB) to predict Texas pharmacists’ intention to report serious adverse drug effects (ADEs) to the Food and Drug Administration (FDA). The study explored the utility of the TPB model constructs (attitude [A], subjective norm [SN], perceived behavioral control [PBC]), as well as past reporting behavior (PRB), and perceived moral obligation (PMO) to predict pharmacists’ intention to report serious ADEs to the FDA. The study also determined if the pharmacists’ A, SN and PBC were related to practice characteristics and demographic factors. A survey was developed based on two focus group interviews, pretested and mailed to 1,500 Texas practicing pharmacists. An overall response rate of 26.4 percent was obtained (n = 377 pharmacists). Overall, pharmacists intended to report serious ADEs, had a favorable attitude towards reporting, were somewhat influenced by social norms regarding reporting and perceived themselves to have some control over reporting serious ADEs to the FDA. For direct measures, A and SN were significant predictors of intention to report serious ADEs, but PBC was not. The TPB constructs together accounted for 34.0 percent of the variance in intention to report serious ADEs to the FDA. Using indirect measures, A, SN and PBC were significant predictors of intention and together accounted for 28.8 percent of the variance in intention to report serious ADEs. PRB and PMO improved the explanatory power of the regression models (direct and indirect measures) over and above the TPB constructs. Unlike most other practice characteristics and demographic factors examined, knowledge was significantly related with the TPB constructs. In summary, A, SN, PBC (indirect measures), PRB, and PMO influence the formation of pharmacists’ intention to report serious ADEs. The TPB has utility in predicting ADE reporting behavior. Pharmacy educators should explore pharmacists’ attitudes, beliefs, and expectations of important others in designing educational programs. Strategies to help pharmacists report more serious ADEs should focus on altering their perception of social pressure towards reporting and addressing the barriers towards ADE reporting (e.g., lack of knowledge).Pharmac

The impact of genetic interactions in antibiotic resistance

Tese de doutoramento, Biologia (Genética), Universidade de Lisboa, Faculdade de Ciências, 2012Genetic interactions, both between genetic material and between this and the surrounding environment of a given individual are important factors for understanding the process of evolution of natural populations. The study of this interactions as well as their integration in evolutionary terms may have several applications such as, for example, understanding the observed prevalence of antibiotic resistance in natural populations. In this thesis the patterns of genetic interactions between multiple-resistances to antibiotics were explored. In particular, epistasis and genotype-by-environment interactions operating among antibiotic resistances were studied. To measure levels of epistasis occurring between multiple-antibiotic-resistances in the complete absence of antibiotics, mutants resistant to three antibiotics commonly used in clinic were first generated: nalidixic acid, rifampicin and streptomycin. With these mutants double resistant mutants were created. By measuring the costs of each mutation individually and jointly the type of epistasis operating between different sets of resistance mutations was determined. The cost of double resistance was majorly lower than expected, revealing the presence of positive epistasis between mutations conferring resistance to the studied antibiotics. The same patterns were observed for interactions between a set of resistance mutations and conjugative plasmids with multiple-resistance factors. However, in this case, extreme cases of positive epistasis coined sign epistasis were observed for a large fraction of combinations. This type of interactions was also observed in the previous study yet less frequently. Naturally occurring bacteria are often faced with a multitude of environments. The action of environmental changes in the effects of antibiotic resistance mutations was studied for a group of mutations resistant to four antibiotics in three environments differing in the CHAPTER I viii number of comprised environmental stresses. This study revealed, for most cases, a strong pattern of interactions between the different genotypes and the environment.As interacções genéticas, quer entre material genético quer entre este e o ambiente que rodeia um determinado organismo, são factores importantes para entender o processo de evolução de populações naturais. O estudo destas interacções bem como a sua integração em termos evolutivos pode ter diversas aplicações tais como, por exemplo, a compreensão da prevalência da resistência a antibióticos observada em populações naturais. Nesta tese exploraram-se os padrões de interacções genéticas entre múltiplas resistências a antibióticos nomeadamente, epistasia e as interacções genótipo-ambiente que ocorrem em resistências a antibióticos. Para medir os níveis de epistasia entre múltiplas resistências a antibióticos na ausência dos mesmos, foram construídos mutantes resistentes a três antibióticos vulgarmente usados em clínica: ácido nalidíxico, rifampicina e estreptomicina. Com estes mutantes foram gerados duplos mutantes. Medindo os custos de cada uma das mutações individualmente e em conjunto determinou-se o tipo de epistasia a operar entre diferentes conjuntos de mutações de resistência. O custo da dupla resistência foi maioritariamente menor do que o esperado, revelando a presença de epistasia positiva entre mutações que conferem resistência aos antibióticos estudados. Os mesmos padrões foram observados para interacções entre um conjunto de mutações que conferem resistência e plasmídeos conjugativos com múltiplos factores de resistência. No entanto, neste caso, foram observados numa larga fracção de combinações casos extremos de epistasia positiva denominados epistasia de sinal, situação também observada anteriormente mas em menor frequência. Na natureza, as bactérias enfrentam frequentemente uma multiplicidade de ambientes. A acção das alterações ambientais nos efeitos das mutações que conferem resistência a antibióticos foi CHAPTER I x estudada num grupo de mutações resistentes a quatro antibióticos em três ambientes que diferem no número de factores ambientais prejudiciais comportados por cada um. Este estudo revelou, para a maioria dos casos, um forte padrão de interacções entre os vários genótipos e o ambiente.Fundação para a Ciência e a Tecnologia (FCT, SFRH/BD/40162/2007

Safety Assessment of Medications in Elderly: Contribution of the Pharmacovigilance System

As a result of the industrialisation and technological and scientific advances in healthcare, there has been a substantial increase in aging of the population worldwide, and Portugal is no exception. In fact, in Portugal, the average life expectancy is increasing and therefore the number of elderly people. Additionally, the proportion of elderly patients with multiple comorbidities is rising, which in turn leads to an increase in medication use and in the risk of adverse drug reactions (ADRs). In fact, ADRs in elderly can be considered a public health problem, having high costs and being a relevant cause of hospitalization and mortality. Pharmacovigilance is the science concerned with the detection, analysis, evaluation, understanding, and prevention of ADRs. It is a fundamental area for the continuous monitoring of the safety of medicines, particularly relevant in the initial periods of the widespread marketing of new drugs, due to relative scarcity of drug safety information available at the time of marketing authorization, which arises, at this stage, essentially based on pre-marketing clinical trials. Pharmacovigilance allows the identification of problems related to the use of drugs, which are often detected in the post-marketing phase. This is essential to prevent and minimize potential iatrogenic risks to the health of patients. Therefore, monitoring the iatrogenicity of medication that particularly affects elderly patients is fundamental to maximize the safety information of medicines in this special population. Additionally, there is an increasing prevalence of elderly patients with diabetes mellitus and musculoskeletal diseases, whereby is important the knowledge generated from real-world pharmacovigilance data to minimize the risk of harm that may occur with drugs used for the treatment of these conditions. The central aim of this work was to characterize the ADRs profile in elderly patients spontaneously reported to the Portuguese Pharmacovigilance System (PPS). Additionally, this work also intended to characterize the ADRs in elderly diabetic patients and to evaluate the safety of non-steroidal anti-inflammatory drugs (NSAIDs) in this age group. For this propose, firstly, all spontaneous ADRs reported to the PPS from 2013 to 2017 were examined. However, considering the aim of this study, ADRs referring to patients aged 65 and over were analysed in higher detail and compared with those reported in non-elderly adults. Secondly, a retrospective analysis of suspected ADRs reports from PPS between 2008 to 2018 was performed, involving patients aged ≥65 years with diabetes mellitus. Finally, it was carried out a comprehensive literature review of NSAIDs safety in elderly patients and, in parallel, considering the same period of time (i.e., 2008-2018), the suspected ADRs related to these drugs reported to a database of pharmacovigilance, for people aged ≥65, were analysed. Reports were analysed in terms of gender of the involved patients, seriousness and type of ADRs, according to the “System Organ Class” from the Medical Dictionary for Regulatory Activities terminology. In the reports with fatal outcome a deeper analysis in terms of “Preferred Term” for each report was performed. In the general analysis of spontaneous reports in the elderly, the most frequent suspected ADRs fall within the categories of general disorders and administration site conditions, and skin and subcutaneous tissue complaints. Regarding the therapeutic agents involved, the antineoplastic drugs were the most commonly implicated. In addition, the antineoplastic and antithrombotic drugs were the most represented pharmacotherapeutic groups of suspected drugs involved in patient’s death. In the analyses of ADRs in elderly diabetic patients, the most frequent were hypoglycaemia and lactic acidosis, and the drugs specifically indicated for glycaemic control were the most frequently involved. Finally, in the literature review performed on NSAIDs safety in elderly patients, most studies concluded that the risk of a gastrointestinal adverse event with the use of cyclooxygenase-2 (COX-2)-selective NSAIDs seems to be lower when compared with conventional NSAIDs. In addition, celecoxib was considered the safest of all other NSAIDs. However, the risk of gastrointestinal events in patients aged ≥75 years taking selective COX-2 inhibitors was higher when compared with younger patients. Additionally, diclofenac was associated with relevant renal adverse events in patients aged 75 years or older as well as in those with some renal impairment. Regarding cardiovascular events the incidence was lower with coxibs than with conventional NSAIDs and celecoxib led to a lower incidence of these events when compared with etoricoxib. In the analysis performed in PPS data most of suspected ADRs had diclofenac as suspected drug. The suspected ADRs most frequently reported fall within the categories of skin and subcutaneous tissue disorders. Serious gastrointestinal ADRs occurred mostly in patients taking more than one NSAID and/or another concomitant drug that increases the incidence of these events, in the absence of gastroprotection. The majority of serious ADRs related to renal and cardiac disorders occurred in patients with history of renal disorders or diabetes mellitus and hypertension, respectively. All the studies performed with the data belonging to PPS concluded that the majority of ADRs were serious, occurred predominantly in female and were expected. Hence, an accurate identification of ADRs, especially the detection of preventable ADRs, is an important starting point to improve drug safety in elderly. Therefore, studies targeting elderly patients are needed to improve the safety information of these drugs in this special population, considering their multiple medical conditions, thus highlighting the importance of active pharmacovigilance. In this context, it is important to emphasize that pharmacovigilance databases are important tools to evaluate issues related to the safety of drugs in older people, enabling to improve the knowledge on the safety profile of medicines in these patients.Com a industrialização e os avanços tecnológicos e científicos na área da saúde, tem-se assistido a um aumento substancial do envelhecimento da população a nível mundial, e Portugal não é exceção. De facto, em Portugal, a esperança média de vida está a aumentar e, consequentemente, o número de idosos. Além disso, a proporção de doentes idosos com múltiplas comorbilidades está a aumentar, o que, por sua vez, leva a um aumento no uso de medicamentos e a um acréscimo do risco de reações adversas a medicamentos (RAMs). Na verdade, as RAMs em idosos podem ser consideradas um problema de saúde pública, com custos elevados, pois são uma causa relevante de hospitalização e mortalidade. A farmacovigilância é a ciência que se centra na deteção, análise, avaliação, compreensão e prevenção de RAMs. É uma área fundamental para a monitorização contínua da segurança dos medicamentos, especialmente relevante nos períodos iniciais da comercialização alargada de novos fármacos, devido à escassez relativa de informação de segurança disponível no momento da autorização de introdução no mercado, a qual advém, nesta fase, essencialmente dos ensaios clínicos conduzidos durante a fase de pré-comercialização. A farmacovigilância permite a identificação de problemas relacionados com o uso de medicamentos, frequentemente detetados apenas na fase de pós-comercialização. Isso é essencial para prevenir e minimizar os riscos iatrogénicos potenciais para a saúde dos doentes. Portanto, monitorizar a iatrogenicidade dos medicamentos, a qual afeta de uma forma mais marcada os doentes idosos, é fundamental para maximizar a informação de segurança dos mesmos nesta população especial. Além disso, há uma prevalência crescente de doentes idosos com quadros clínicos de multipatologia, incluindo a presença de diabetes mellitus e doenças músculo-esqueléticas, sendo importante o conhecimento gerado a partir dos dados de farmacovigilância obtidos em contexto de vida real para minimizar os riscos decorrentes do uso de medicamentos nestas condições. O objetivo central deste trabalho consistiu na caraterização do perfil de RAMs em doentes idosos, em Portugal, notificadas espontaneamente ao Sistema Nacional de Farmacovigilância (SNF). Adicionalmente, esta tese contemplou também a caracterização das RAMs em doentes idosos diabéticos e a avaliação da segurança dos fármacos anti-inflamatórios não esteroides (AINEs) nesta faixa etária. Para tal, em primeiro lugar, foram avaliadas todas as RAMs comunicadas ao SNF de 2013 a 2017. No entanto, considerando o objetivo deste estudo, as RAMs referentes a doentes com 65 ou mais anos foram analisadas detalhadamente e comparadas com as que foram notificadas em adultos não idosos. Em segundo lugar, foi realizada uma análise retrospetiva das notificações de suspeitas de RAMs submetidas ao SNF entre 2008 e 2018, envolvendo doentes com idade ≥65 anos com diabetes mellitus. Por fim, foi realizada uma revisão compreensiva da literatura sobre a segurança dos AINEs em doentes idosos e, em paralelo, considerando o mesmo período de tempo (i.e., 2008-2018) foram analisadas as suspeitas de RAMs relacionadas com este tipo de medicamentos, manifestadas em indivíduos com 65 ou mais anos e notificadas para o SNF. As notificações foram analisadas relativamente ao género dos doentes envolvidos, gravidade e tipo de RAMs, de acordo com a terminologia “Classe de Sistemas e Órgãos” do dicionário médico para a atividade regulamentar. Nos casos com desfecho fatal, foi realizada uma análise mais aprofundada em termos do “Termo Preferencial” para cada caso. Na análise geral das notificações espontâneas em idosos, as RAMs mais frequentes enquadraram-se nas categorias de distúrbios gerais e perturbações no local de administração e afeções da pele e do tecido subcutâneo. Em relação aos grupos terapêuticos envolvidos, os medicamentos antineoplásicos foram os mais comumente implicados. Além disso, os medicamentos antineoplásicos e antitrombóticos foram os grupos farmacoterapêuticos mais representados entre os medicamentos suspeitos envolvidos na morte de doentes. Mediante análise das RAMs em doentes idosos diabéticos, as mais frequentes foram a hipoglicémia e a acidose láctica, sendo os medicamentos especificamente indicados para o controlo glicémia os mais frequentemente envolvidos. Finalmente, tendo em conta a revisão da literatura realizada referente à segurança de AINEs em doentes idosos, a maioria dos estudos concluiu que o risco de um evento adverso gastrointestinal é inferior com o uso de AINEs seletivos para a isoenzima cicloxigenase-2 (COX-2) do que com o uso de AINEs convencionais. Mais especificamente, entre os AINEs, o celecoxib foi considerado o fármaco mais seguro. No entanto, o risco de eventos gastrointestinais em doentes com idade ≥75 anos a tomar AINEs seletivos para COX-2 foi maior que o observado em doentes mais jovens. Além disso, o diclofenac foi associado a eventos adversos renais relevantes em doentes com 75 ou mais anos, bem como naqueles com algum grau de insuficiência renal. Em relação aos eventos adversos cardiovasculares, a sua incidência foi menor com os coxibes do que com os AINEs convencionais, e o celecoxib levou a uma incidência menor desses eventos quando comparado ao etoricoxib. Em resultado da análise realizada aos dados do SNF, foi possível constatar que a maioria das suspeitas de RAMs envolveu o diclofenac. As suspeitas de RAMs mais frequentemente relatadas enquadraram-se nas categorias de afeções da pele e do tecido subcutâneo. As RAMs gastrointestinais graves ocorreram principalmente em doentes a tomar mais que um AINE e/ou outro medicamento concomitante, o que aumenta a incidência desses eventos, na ausência de gastroproteção. A maioria das RAMs graves relacionadas com distúrbios renais ou distúrbios cardíacos ocorreram em doentes com história clínica de distúrbios renais ou diabetes mellitus e de hipertensão arterial, respetivamente. Todos os estudos realizados com os dados do SNF que suportam esta tese concluíram que a maioria das RAMs eram graves, ocorreram predominantemente em mulheres e eram expetáveis. A identificação exata de RAMs, especialmente a deteção de RAMs evitáveis, é um ponto de partida importante para melhorar a segurança dos medicamentos em idosos. Portanto, estudos direcionados para a população geriátrica são necessários para melhorar a informação de segurança desses medicamentos nesta população especial, considerando as suas múltiplas condições médicas, destacando-se assim a importância da farmacovigilância ativa. Nesse contexto, é importante enfatizar que as bases de dados de farmacovigilância são ferramentas importantes para avaliar questões relacionadas com a segurança dos medicamentos em idosos, possibilitando aprimorar o conhecimento sobre o perfil de segurança de medicamentos nestes doentes

Translational biomedical informatics and pharmacometrics approaches in the drug interactions research

Drug interaction is a leading cause of adverse drug events and a major obstacle for current clinical practice. Pharmacovigilance data mining, pharmacokinetic modeling, and text mining are computation and informatic tools on integrating drug interaction knowledge and generating drug interaction hypothesis. We provide a comprehensive overview of these translational biomedical informatics methodologies with related databases. We hope this review illustrates the complementary nature of these informatic approaches and facilitates the translational drug interaction research

Clinical risk modelling with machine learning: adverse outcomes of pregnancy

As a complex biological process, there are various health issues that are related to pregnancy. Prenatal care, a type of preventative healthcare at different points in gestation is comprised of management, treatment, and mitigation of such issues. This also includes risk prediction for adverse pregnancy outcomes, where probabilistic modelling is used to calculate individual’s risk at the early stages of pregnancy. This type of modelling can have a definite clinical scope such as in prenatal screening, and an educational aim where awareness of a healthy lifestyle is promoted, such as in health education. Currently, the most used models are based on traditional statistical approaches, as they provide sufficient predictive power and are easily interpreted by clinicians. Machine learning, a subfield of data science, contains methods for building probabilistic models with multidimensional data. Compared to existing prediction models related to prenatal care, machine learning models can provide better results by fitting more intricate nonlinear decision boundary areas, improve data-driven model fitting by generating synthetic data, and by providing more automation for routine model adjustment processes. This thesis presents the evaluation of machine learning methods to prenatal screening and health education prediction problems, along with novel methods for generating synthetic rare disorder data to be used for modelling, and an adaptive system for continuously adjusting a prediction model to the changing patient population. This way the thesis addresses all the four main entities related to predicting adverse outcomes of pregnancy: the mother or patient, the clinician, the screening laboratory and the developer or manufacturer of screening materials and systems.Kliinisen riskin mallinnus koneoppimismenetelmin: raskaudelle haitalliset lopputulemat Raskaus on kompleksinen biologinen prosessi, jonka etenemiseen liittyy useita terveysongelmia. Äitiyshoito voidaan kuvata ennalta ehkäiseväksi terveydenhuolloksi, jossa pyritään käsittelemään, hoitamaan ja lievittämään kyseisiä ongelmia. Tähän hoitoon sisältyy myös raskauden haitallisten lopputulemien riskilaskenta, missä probabilistista mallinnusta hyödynnetään määrittämään yksilön riski raskauden varhaisissa vaiheissa. Tällä mallinnuksella voi olla selkeä kliininen tarkoitus kuten prenataaliseulonta, tai terveyssivistyksellinen tarkoitus missä odottavalle äidille esitellään raskauden kannalta terveellisiä elämäntapoja. Tällä hetkellä eniten käytössä olevat ennustemallit perustuvat perinteiseen tilastolliseen mallinnukseen, sille ne tarjoavat riittävän ennustetehokkuuden ja ovat helposti tulkittavissa. Koneoppiminen on datatieteen osa-alue, joka pitää sisällään menetelmiä millä voidaan mallintaa moniulotteista dataa ennustekäyttöön. Verrattuna olemassa oleviin äitiyshoidon ennustemalleihin, koneoppiminen mahdollistaa parempien ennustetulosten tuottamisen sovittamalla hienojakoisempia epälineaarisia päätösalueita, tehostamalla datakeskeisten mallien sovitusta luomalla synteettisiä havaintoja ja tarjoamalla enemmän automaatiota rutiininomaiseen mallien hienosäätöön. Tämä väitös esittelee koneoppimismenetelmien evaluaation prenataaliseulonta-ja terveyssivistysongelmiin, ja uusia menetelmiä harvinaisten sairauksien datan luomiseen mallinnustarkoituksiin ja jatkuvan ennustemallin hienosäätämisen järjestelmän muuttuvia potilaspopulaatiota varten. Näin väitös käy läpi kaikki neljä asianomaista jotka liittyvät haitallisten lopputulemien ennustamiseen: odottava äiti eli potilas, kliinikko, seulontalaboratorio ja seulonnassa käytettävien materiaalien ja järjestelmien kehittäjä tai valmistaja

Cognitive-behavioral therapy for obsessive-compulsive disorder: access to treatment, prediction of long-term outcome with neuroimaging.

This article reviews issues related to a major challenge to the field for obsessive-compulsive disorder (OCD): improving access to cognitive-behavioral therapy (CBT). Patient-related barriers to access include the stigma of OCD and reluctance to take on the demands of CBT. Patient-external factors include the shortage of trained CBT therapists and the high costs of CBT. The second half of the review focuses on one partial, yet plausible aid to improve access - prediction of long-term response to CBT, particularly using neuroimaging methods. Recent pilot data are presented revealing a potential for pretreatment resting-state functional magnetic resonance imaging and magnetic resonance spectroscopy of the brain to forecast OCD symptom severity up to 1 year after completing CBT