Pharmacovigilance & Drug Safety

Pharmacology & Drug Development includes developing drugs for rare disease can be challenging due to specific rare disease characteristics. The French Medical Pharmacology is structured and positioned to play a major role in Orphan Drug Research and Development due to the required expertise concentrated into pharmacology departments. Consequence, this intra and multidisciplinary expertise offers all resource to elaborate a tailored approach for orphan drug development, in new entities as well as in repositioning. For preclinical development: drug screening, candidate selection (taking into account PK, metabolism, variability, potential toxicity), preclinical models (IPS, animal models) that could allow a better translation to human research.

Pharmacovigilance , also known as drug safety, is the pharmacological science relating to the collection, detection, assessment, monitoring, and prevention of adverse effects with pharmaceutical products.The etymological roots for the word "pharmacovigilance" are: pharmakon and vigilare  As such, pharmacovigilance heavily focuses on adverse drug reactions, or ADRs, which are defined as any response to a drug which is noxious and unintended, including lack of efficacy (the condition that this definition only applies with the doses normally used for the prophylaxis, diagnosis or therapy of disease, or for the modification of physiological disorder function was excluded with the latest amendment of the applicable legislation).Medication errors such as overdose, and misuse and abuse of a drug as well as drug exposure during pregnancy and breastfeeding, are also of interest, even without an adverse event, because they may result in an adverse drug reaction.

Risk management in pharmacovigilance is undertaken to promote safe use of medicines and safeguard health of patients. It is a set of activities performed for identification of risk, risk assessment, and risk minimization and prevention. Risk management has the following stages: identification and characterization of the safety profile of the medicinal product; planning of pharmacovigilance activities to characterize risks and identify new risks; planning and implementation of risk minimization and mitigation and assessment of the effectiveness of these activities; and document postapproval obligations that have been imposed as a condition of the marketing authorization.

Case report form (CRF) is a specialized document in clinical research. It should be study protocol driven, robust in content and have material to collect the study specific data. Though paper CRFs are still used largely, use of electronic CRFs are gaining popularity due to the advantages they offer such as improved data quality, online discrepancy management and faster database lock etc. Main objectives behind CRF development are preserving and maintaining quality and integrity of data. CRF design should be standardized to address the needs of all users such as investigator, site coordinator, study monitor, data entry personnel, medical coder and statistician. Data should be organized in a format that facilitates and simplifies data analysis. Collection of large amount of data will result in wasted resources in collecting and processing it and in many circumstances, will not be utilized for analysis.

Clinical trials involve the efficacy of new drugs for a disease which have no proven effective therapy. The studies are experimented by animal models, animal and human subjects. It emphasizes the unconventional design of drugs, results of clinical trials, statistical methods, methodology of operation, data management, ethical and legal considerations.

JCTRA has a broad coverage of articles pharmaceutical development, intellectual property rights and regulatory affairs that approaches appropriate for advancing drug development. It also publishes methodologies, protocols, result papers, commentaries and controversial issues.

This chapter covers the discipline and practice of Data Quality Management (DQM) in a multi-domain Master Data Management (MDM) framework. It discusses how to define and apply a DQM model consistently across a multi-domain environment, and how to expand the practice of DQM to an enterprise level. This chapter starts by presenting how DQM fits into a multi-domain MDM environment and how important it is to manage DQM strategies, decisions, and execution. It continues by introducing a DQM model that is critical to supporting and scaling the discipline beyond MDM. Finally, it covers a data-quality improvement life cycle, with the required steps and activities to analyze, plan, execute, and monitor data quality projects effectively and efficiently.

The objective of this study is to estimate the prevalence and describe the characteristics of pDDIs in medical prescriptions of hospitalized surgical patients. In this cross-sectional study, we analyzed 370 medical prescriptions from the surgery unit of a Mexican public teaching hospital. The identification and classification of potential drug-drug interactions were performed with the Micromedex 2.0 electronic drug information database. Results were analyzed with descriptive statistics and we estimated OR (odds ratio) to determine associated risk factors.

For several reasons, vaccines and biologicals require modified systems of safety monitoring. They are often administered to healthy children. This applies particularly to vaccines used within a national immunization programme. In many countries, those exposed to a particular vaccine represent the entire birth cohort and therefore a sizeable part of the entire population. People’s hopes of safety are high, and they are reluctant to countenance even a small risk of adverse events. Disquiets regarding vaccine safety, real or imagined, may result in loss of confidence in entire vaccine programmes. This can result in poor compliance and a consequent resurgence in morbidity and mortality of vaccine-preventable disease. It is essential that there should be adequate safety investigation supporting immunization programmes. The skills and organization to deal with genuine adverse events are essential in preventing or managing misplaced fear caused by false or unproven signals from patients and health workers that might adversely affect immunization cover. For example, concerns about the safety of whole-cell Pertussis resulted in dramatic reductions in vaccines coverage and a resurgence of Pertussis in many countries.

Signal detection involves a range of techniques. The WHO defines a safety signal as: "Reported information on a possible causal connection between an adverse event and a drug, the relationship being unknown or incompletely documented previously". Commonly more than a single report is required to generate a signal, depending upon the event and quality of the information available.

Data mining pharmacovigilance databases is one approach that has become increasingly popular with the availability of extensive data sources and low-cost computing resources. The data sources may be owned by a pharmaceutical company, a drug regulatory authority, or a large healthcare provider. Individual Case Safety Reports (ICSRs) in these databases are retrieved and converted into structured format, and statistical methods (usually a mathematical algorithm) are applied to calculate statistical measures of association. If the statistical measure crosses an arbitrarily set threshold, a signal is declared for a given drug associated with a given adverse event. All signals deemed worthy of exploration, require further analysis using all available data in an attempt to confirm or refute the signal. If the analysis is inconclusive, extra data may be needed such as a post-marketing observational trial.