127 Good Manufacturing Practice (GMP) courses in Cardiff delivered Online

This course describes the requirements that must be met by, and options available to, the sponsor during the conduct of an authorised clinical trial. It identifies the various interactions with MSCs that occur via the Clinical Trials Information System (CTIS), and it summarises and links to the extensive guidance available from the European Commission and the European Medicines Agency. Its companion course CT11 sets out the European legal and regulatory context for clinical trials and describes how to apply via the CTIS for authorisation to conduct trials. The two courses therefore provide an ideal foundation for understanding and complying with the new law.

Pharmaceutical and biotechnology companies and researchers need to assure regulatory authorities of the reliability of the data that they generate or acquire during product development and manufacturing – that is, to demonstrate data integrity. Data integrity is assessed during regulatory inspections of manufacturing and research sites. Inadequacies of data integrity are frequently reported by inspectors and result in regulatory actions against the companies or individuals concerned. Practices that assure data integrity are required by law and/or expected by regulators in the fields of nonclinical and clinical research, manufacturing and distribution, and pharmacovigilance of medicinal products. This course explains the requirements and describes principles and practices that should be followed to assure regulators and contractual partners of data integrity in the manufacture of medicinal products.

This module provides an introduction to the basics of medical device regulation, especially the requirements that manufacturers must meet in order to market devices in Europe and the USA.

Pharmaceutical, biotechnology and medical device companies and clinical researchers need to assure regulatory authorities of the reliability of the data that they generate during product development and testing – that is, to demonstrate data integrity. Practices that provide assurance of data integrity in clinical research are required by law and/or established as expectations in regulatory guidance. The data are reviewed in regulatory applications or during regulatory inspections of clinical trial sponsor and investigational sites. Inadequacies of data integrity are frequently reported by inspectors and result in regulatory actions against the organizations or individuals concerned. This course explains the requirements and describes principles and practices that should be followed by trial sponsors, investigators and other clinical research personnel to assure regulators of data integrity.

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Pharmacoepidemiology is the study of the use and effects of drugs in large numbers of people. It provides a bridge between clinical pharmacology and epidemiology. The increasing demand for real-world evidence of the safety, efficacy and utility of medicinal products has focused greater attention on pharmacoepidemiological research. This module will help those who plan and conduct such research, and analyse and report the findings, to follow good practice.

A company’s Corrective and Preventive Action (CAPA ) system establishes how personnel should deal with manufacturing problems that have occurred or that may occur if not prevented. This module explains the principles of corrective and preventive action and describes typical CAPA procedure. It goes on to introduce root cause analysis and outline the role of progress tracking, escalating, and trending of CAPA procedures.

This module will introduce you to monoclonal antibodies, explaining how they work, how they are made, and the many uses to which they are put.

An Urgent Safety Restriction (USR) is a regulatory action taken, in response to a safety signal, to make an interim change to the terms of the marketing authorisation for a medicinal product in Europe. This module describes the principles and procedures for USRs.

Analytical statistical elements are essential concepts in the design of clinical trials. This analysis helps us to understand whether a conclusion from a study of a sample of the target population applies generally to that population as a whole. In particular, it helps us to answer the question: Did the treatment effect in the given study occur just by chance? The statistical elements of a well-controlled study minimise the chances of drawing the wrong conclusions, by providing clear thresholds for such errors. The basic statistical elements of a clinical trial include eligibility criteria, randomisation, sample size, power, and blinding, and these are discussed in this short course.