Barriers in reporting adverse effects of medical devices: a literature review.

Medical devices play an essential role in the delivery of healthcare but its use is not entirely risk free. There are several instances where it causes mortality or morbidity among users. It is important to evaluate the risks involved at every stage of its application to bring improvement in the standard of healthcare. For the purpose Materiovigilance Program of India was launched on July 6, 2015. Despite these efforts, available data suggests that reporting of adverse events is very low. The present study aims to identify barriers that influence the reporting of adverse events of medical devices and outline a strategy to overcome these barriers. Systemic review method has been adopted to achieve these ends. Thirty-one papers have been selected based on the inclusion criteria related to objective of the study. Lack of awareness, attitude, and resources are found to be major barriers at the individual level for not reporting adverse effects of medical devices. The organizational factors such as hierarchical set up, lack of time and incentives, and furthermore lack of industry responsiveness have been identified as prominent barriers to the reporting of adverse events. In order to improve the reporting level, it is important to make access and contact easier with the reporting system. Engaging healthcare professionals at various levels by acknowledging and appreciating their contribution. The adverse events of medical devices should not be restricted to physicians; only rather other health care professional such as nurses, pharmacists, and technicians should also be encouraged to report any adverse event of medical devices.

More than red tape: exploring complexity in medical device regulatory affairs.

Introduction: This study investigates the complexity of regulatory affairs in the medical device industry, a critical factor influencing market access and patient care. Methods: Through qualitative research, we sought expert insights to understand the factors contributing to this complexity. The study involved semi-structured interviews with 28 professionals from medical device companies, specializing in various aspects of regulatory affairs. These interviews were analyzed using a mix of qualitative coding and natural language processing (NLP) techniques. Results: The findings reveal key sources of complexity within the regulatory landscape, divided into five domains: (1) regulatory language complexity, (2) intricacies within the regulatory process, (3) global-level complexities, (4) database-related considerations, and (5) product-level issues. Discussion: The participants highlighted the need for strategies to streamline regulatory compliance, enhance interactions between regulatory bodies and industry players, and develop adaptable frameworks for rapid technological advancements. Emphasizing interdisciplinary collaboration and increased transparency, the study concludes that these elements are vital for establishing coherent and effective regulatory procedures in the medical device sector.

Evolution of Drug Development and Regulatory Affairs: The Demonstrated Power of Artificial Intelligence.

PURPOSE: Artificial intelligence (AI) refers to technology capable of mimicking human cognitive functions and has important applications across all sectors and industries, including drug development. This has considerable implications for the regulation of drug development processes, as it is expected to transform both the way drugs are brought to market and the systems through which this process is controlled. There is currently insufficient evidence in published literature of the real-world applications of AI. Therefore, this narrative review investigated, collated, and elucidated the applications of AI in drug development and its regulatory processes. METHODS: A narrative review was conducted to ascertain the role of AI in streamlining drug development and regulatory processes. FINDINGS: The findings of this review revealed that machine learning or deep learning, natural language processing, and robotic process automation were favored applications of AI. Each of them had considerable implications on the operations they were intended to support. Overall, the AI tools facilitated access and provided manageability of information for decision-making across the drug development lifecycle. However, the findings also indicate that additional work is required by regulatory authorities to set out appropriate guidance on applications of the technology, which has critical implications for safety, regulatory process workflow and product development costs. IMPLICATIONS: AI has adequately proven its utility in drug development, prompting further investigations into the translational value of its utility based on cost and time saved for the delivery of essential drugs.

Overdosage Section in US and EU Labeling.

The Prescribing Information (PI) in the United States (US) and the Summary of Product Characteristics (SmPC) in the European Union (EU) are approved by the US Food & Drug Administration (FDA), and the European Medicines Agency (EMA), respectively. The inclusion of overdosage information in these documents is a regulatory requirement in both regions. This research evaluates the content of the overdosage section of US and EU labeling. The overdosage sections of labels for drugs approved in the US in three time periods were analyzed: 2000-2001, 2010-2011, and 2020-2021. EU labels for these same products were also reviewed if registered through the Centralized Procedure. Data collection and analyses were performed using a predefined questionnaire, focusing on adherence to regulatory requirements and identifying areas where additional regulatory guidance may be beneficial. The findings indicate that the content of the overdosage sections largely comply with the regulatory requirements of their respective regions. Fewer than half of the labels included information on supratherapeutic doses observed from clinical studies, risk factors for overdose or population specific data associated with overdose. Inconsistencies were noted concerning the incorporation of animal data when human data were available, in addition to the referencing of Poison Centers. The overall utility of non-specific treatment recommendations, in addition to gastric lavage is discussed. While the content of the overdosage section generally aligns with regulatory expectations, additional regulatory guidance could enhance consistency in how this section of labeling is presented and clarify expectations to improve its usefulness for health care professionals (HCPs).

Insight into the Functional Dynamics and Challenges of Exosomes in Pharmaceutical Innovation and Precision Medicine.

Of all the numerous nanosized extracellular vesicles released by a cell, the endosomal-originated exosomes are increasingly recognized as potential therapeutics, owing to their inherent stability, low immunogenicity, and targeted delivery capabilities. This review critically evaluates the transformative potential of exosome-based modalities across pharmaceutical and precision medicine landscapes. Because of their precise targeted biomolecular cargo delivery, exosomes are posited as ideal candidates in drug delivery, enhancing regenerative medicine strategies, and advancing diagnostic technologies. Despite the significant market growth projections of exosome therapy, its utilization is encumbered by substantial scientific and regulatory challenges. These include the lack of universally accepted protocols for exosome isolation and the complexities associated with navigating the regulatory environment, particularly the guidelines set forth by the U.S. Food and Drug Administration (FDA). This review presents a comprehensive overview of current research trajectories aimed at addressing these impediments and discusses prospective advancements that could substantiate the clinical translation of exosomal therapies. By providing a comprehensive analysis of both the capabilities and hurdles inherent to exosome therapeutic applications, this article aims to inform and direct future research paradigms, thereby fostering the integration of exosomal systems into mainstream clinical practice.

Extracellular Vesicles as Next-Generation Diagnostics and Advanced Therapy Medicinal Products.

Extracellular vesicles (EVs) hold great promise for clinical application as new diagnostic and therapeutic modalities. This paper describes major GMP-based upstream and downstream manufacturing processes for EV large-scale production, also focusing on post-processing technologies such as surface bioengineering and uploading studies to yield novel EV-based diagnostics and advanced therapy medicinal products. This paper also focuses on the quality, safety, and efficacy issues of the bioengineered EV drug candidates before first-in-human studies. Because clinical trials involving extracellular vesicles are on the global rise, this paper encompasses different clinical studies registered on clinical-trial register platforms, with varying levels of advancement, highlighting the growing interest in EV-related clinical programs. Navigating the regulatory affairs of EVs poses real challenges, and obtaining marketing authorization for EV-based medicines remains complex due to the lack of specific regulatory guidelines for such novel products. This paper discusses the state-of-the-art regulatory knowledge to date on EV-based diagnostics and medicinal products, highlighting further research and global regulatory needs for the safe and reliable implementation of bioengineered EVs as diagnostic and therapeutic tools in clinical settings. Post-marketing pharmacovigilance for EV-based medicinal products is also presented, mainly addressing such topics as risk assessment and risk management.

AI Through Ethical Lenses: A Discourse Analysis of Guidelines for AI in Healthcare.

While the technologies that enable Artificial Intelligence (AI) continue to advance rapidly, there are increasing promises regarding AI's beneficial outputs and concerns about the challenges of human-computer interaction in healthcare. To address these concerns, institutions have increasingly resorted to publishing AI guidelines for healthcare, aiming to align AI with ethical practices. However, guidelines as a form of written language can be analyzed to recognize the reciprocal links between its textual communication and underlying societal ideas. From this perspective, we conducted a discourse analysis to understand how these guidelines construct, articulate, and frame ethics for AI in healthcare. We included eight guidelines and identified three prevalent and interwoven discourses: (1) AI is unavoidable and desirable; (2) AI needs to be guided with (some forms of) principles (3) trust in AI is instrumental and primary. These discourses signal an over-spillage of technical ideals to AI ethics, such as over-optimism and resulting hyper-criticism. This research provides insights into the underlying ideas present in AI guidelines and how guidelines influence the practice and alignment of AI with ethical, legal, and societal values expected to shape AI in healthcare.

Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices.

The use of AI in healthcare has sparked much debate among philosophers, ethicists, regulators and policymakers who raised concerns about the implications of such technologies. The presented scoping review captures the progression of the ethical and legal debate and the proposed ethical frameworks available concerning the use of AI-based medical technologies, capturing key themes across a wide range of medical contexts. The ethical dimensions are synthesised in order to produce a coherent ethical framework for AI-based medical technologies, highlighting how transparency, accountability, confidentiality, autonomy, trust and fairness are the top six recurrent ethical issues. The literature also highlighted how it is essential to increase ethical awareness through interdisciplinary research, such that researchers, AI developers and regulators have the necessary education/competence or networks and tools to ensure proper consideration of ethical matters in the conception and design of new AI technologies and their norms. Interdisciplinarity throughout research, regulation and implementation will help ensure AI-based medical devices are ethical, clinically effective and safe. Achieving these goals will facilitate successful translation of AI into healthcare systems, which currently is lagging behind other sectors, to ensure timely achievement of health benefits to patients and the public.

Polish regulatory system regarding ATMP hospital exemptions.

Introduction: This article explains the current regulatory system in Poland regarding Advanced Therapy Medicinal Products given under Hospital Exemptions (ATMP-HE). Methods: The relevant sections of Polish legislation are translated into English and their interaction is described. Results: We analyze the impact of these regulations from the perspective of three stakeholder groups: manufacturers, physicians, and patients. Amendments enacted between 2018 and 2023 have substantially changed Polish implementation of the ATMP-HE pathway. In Poland, most ATMP-HE treatments have been therapies employing Mesenchymal Stromal Cells (MSC). Discussion: Comparison to other European countries shows that Poland is within the mainstream of EU practices regarding ATMP-HE implementation. One notable issue is that Poland has relatively low per capita spending on healthcare, and ATMP-HE in Poland must be funded from outside the government healthcare system. Conclusions. The original intention of the legislation that created ATMP-HE was to allow access to experimental therapies for patients with unmet needs. It remains to be seen if that mission can be fulfilled amidst conflicting pressures from various stakeholder groups.

Development of Cell and Gene Therapies for Clinical Use in the US and EU: Summary of Regulatory Guidelines.

Recent decades have seen advancements in the management and treatment of difficult-- to-treat diseases such as cancer. A special class of therapeutics called cell and gene therapy has been introduced in the past 10 years. Cell and gene therapy products have strengthened the treatment options for life-threatening diseases with unmet clinical needs and also provided the possibility of a potential cure for the disease in some of the patients. Cell and gene therapy products are gaining recognition, and the interest in clinical development of cell and gene therapy products is increasing. Moreover, as the class of cell and gene therapy products is relatively new, there is a limited regulatory experience in the development, and the developers of the cell and gene therapy products can often be puzzled with an array of questions on regulations. The current review intends to provide a basic understanding of regulatory guidelines from the FDA and EMA that are applicable to cell and gene therapy products. Essentials such as which office is responsible for the evaluation of applications, which regulatory class/pathway is appropriate for development, and what are the quality, nonclinical and clinical studies that are needed to support the application are discussed in the article. In addition, a summary of regulatory designations and the post-approval requirements, such as Risk Evaluation and Mitigation Strategies (REMS) and long-term follow- up, is included in the article. Developers (referred to as 'sponsors' in this article) of cell and gene therapies can use the respective guidance documents and other specific review articles cited in this review for detailed information on the topics.

Why Pharmacovigilance of Non-steroidal Anti-inflammatory Drugs is Important in India?

BACKGROUND: Non-steroidal Anti-Inflammatory Drugs (NSAIDs) are among the drugs that are most regularly administered to manage inflammation and pain. Over-the-Counter (OTC) NSAIDs are widely accessible, particularly in developing countries like India. This casual approach to using NSAIDs may operate as a magnet for NSAID-related adverse drug reactions (ADRs) among patients. OBJECTIVES: As patients in India are less informed about the appropriate use of NSAIDs and consumption patttern, adverse drug reactions, and the importance of reporting ADRs, the current study's objective is to promote patient safety by using pharmacovigilance as a tool to educate patients. METHODS: A targeted literature methodology was utilized to gather the data pertaining to NSAIDs, their ADRs and their pharmacovigilance. Different scientific databases, such as Science Direct, PubMed, Wiley Online Library, Springer, and Google Scholar, along with authentic textbooks, were explored as reference literature. RESULTS: In general, NSAIDs consumption pattern depends upon the different age groups. Around 1.6 billion tablets of NSAIDs are consumed in India for ailments, such as headaches, arthritis, menstrual cramps, osteoarthritis, back pain, rheumatoid arthritis, gout, osteoporosis, tendinitis, cancer pain and chronic pain. Common ADRs of NSAIDs include nausea, vomiting, headache, gastritis, abdominal pain, and diarrhoea. Also, they can cause renal damage and cardiovascular problems if not consumed in a dose-dependent manner. However, Diclofenac and Ibuprofen have both been linked to depression and dementia. There have been reports of aplastic anaemia, agranulocytosis linked to phenylbutazone, Stevens-Johnson, and Lyell's syndrome linked to isoxicam and piroxicam, as well as the vulnerability of new-borns to Reye's syndrome after aspirin use. Lack of awareness, time constraints and unpredictability, poor training in ADRs identification, etc., are some of the reasons for the under-reporting of ADR of NSAIDs in India. CONCLUSION: In order to rationally prescribe NSAIDs, it is essential to be aware of probable ADR's and establish prescription guidelines. Prescribers' behaviour can be changed toward excellent prescribing practices by conducting routine prescription assessments dealing with NSAIDs and providing feedback. In the near future, it will be critical to strengthen ADR data management and expand the reach of pharmacovigilance programs, ADR monitoring centers, and healthcare professionals' especially pharmacists' training in rural locations.

Biomedical, socio-behavioral, and implementation science gaps in multipurpose prevention technology research.

There is strong global need for the development of Multipurpose Prevention Technologies (MPTs) that prevent HIV, pregnancy, and/or other sexually transmitted infections (STIs). However, despite decades of research focused on the development of MPTs, numerous research gaps remain, contributing to reproductive health disparities. This commentary will highlight biomedical, socio-behavioral, and implementation science gaps in MPT research. Biomedical gaps and barriers include limited dosage forms, challenges around drug selection and stable coformulation of multiple drugs, and an unclear regulatory pathway. Behavioral, social, and structural gaps include lack of research around MPT preferences for some subgroups of potential end users, lack of knowledge around whether MPTs improve uptake, adherence, and persistence vs. separate products, and a need to further understand how social and cultural factors might impact MPT interest and use. Gaps in implementation science research will need to be addressed to better understand how to implement MPTs to maximize effectiveness and benefit. This commentary will also identify opportunities for integrating biomedical and behavioral science around MPTs.

Real-time algorithmic exchange and processing of pharmaceutical quality data and information.

Herein, a modern method is proposed for exchanging and processing real-time medicinal product information using Health Level 7 International's (HL7) Fast Healthcare Interoperability Resources (FHIR®) standard, Application Programming Interfaces (API), digitization and artificial intelligence. FHIR is presently in use largely to facilitate interactions between patient-facing healthcare institutions, such as hospitals, doctor's offices, and laboratories, for electronic health record management and exchange. There are several ongoing efforts to adapt the FHIR standard for regulatory use cases to support the needs of the global biopharmaceutical industry, including the exchange of Electronic Product Information (ePI); chemistry, manufacturing, and controls (CMC) data; and adverse event reporting. Once in place, this new method of data exchange is expected to (1) improve efficiency by reducing the time and effort needed to manage regulatory information; (2) accelerate decision making; (3) encourage innovation in pharmaceutical manufacturing; (4) improve the ability and agility of information exchange. Currently, the end-to-end timescale for the pharmaceutical regulatory workflow is measured in months and years. This new paradigm will use FHIR APIs and other supporting technologies to reduce the potential time for data exchange from months to days, hours, minutes, and eventually sub-seconds. With such drastic improvements in speed provided by digitization, automation, and interoperability, the biopharmaceutical industry can reach more patients, and more quickly than at any time in the industry's 100+ year history. The present work will focus on examining specific real-world implementation examples for using FHIR to support exchange of CMC information within and across the biopharmaceutical industry.

Harmonising nomenclature in pharmacopeial texts.

Nomenclature has always been a source of debate in the scientific literature. In the context of pharmaceutical regulation, varying interpretations of technical language can emerge due to philosophical or linguistic differences between two expert groups, which may undo efforts to harmonise regulatory approval mechanisms for new medicines. This letter describes three examples of divergence within pharmacopeial texts produced in the US, EU and Japan and suggests how these have emerged. Ultimately, I advocate for a consensus and an all agreed upon terminology that would be helpful for the global pharmaceutical industry, as opposed to many agreements between individual manufacturers and regulators of medicines, which may reintroduce variation in regulatory standards.

Unlock the algorithms: regulation of adaptive algorithms in reproduction.

In the USA, the Food and Drug Administration plans to regulate artificial intelligence and machine learning software systems as medical devices to improve the quality, consistency, and transparency of their performance across specific age, racial, and ethnic groups. Embryology procedures do not fall under the federal regulation of "CLIA 88." They are not tests per se; they are cell-based procedures. Likewise, many add-on procedures related to embryology, such as preimplantation genetic testing, are considered "laboratory-developed tests" and are not subject to Food and Drug Administration regulation at present. Should predictive artificial intelligence algorithms in reproduction be considered medical devices or laboratory-developed tests? Certain indications certainly carry a higher risk, such as medication dosage, where the consequences of mismanagement could be severe, whereas others, such as embryo selection, are noninterventional (selecting from a patient's own embryos and the course of treatment does not change) and present little to no risk. The regulatory landscape is complex, involving data diversity and performance, real-world evidence, cybersecurity, and postmarket surveillance.

Validation of Artificial Intelligence Containing Products Across the Regulated Healthcare Industries.

PURPOSE: The introduction of artificial intelligence / machine learning (AI/ML) products to the regulated fields of pharmaceutical research and development (R&D) and drug manufacture, and medical devices (MD) and in vitro diagnostics (IVD), poses new regulatory problems: a lack of a common terminology and understanding leads to confusion, delays and product failures. Validation as a key step in product development, common to each of these sectors including computerized systems and AI/ML development, offers an opportune point of comparison for aligning people and processes for cross-sectoral product development. METHODS: A comparative approach, built upon workshops and a subsequent written sequence of exchanges, is summarized in a look-up table suitable for mixed-teams work. RESULTS: 1. A bottom-up, definitions led, approach which leads to a distinction between broad vs narrow validation, and their relationship to regulatory regimes. 2. Common basis introduction to the primary methodologies for software validation, including AI-containing software validation. 3. Pharmaceutical drug development and MD/IVD-specific perspectives on compliant AI software development, as a basis for collaboration. CONCLUSIONS: Alignment of the terms and methodologies used in validation of software products containing artificial intelligence/machine learning (AI/ML) components across the regulated industries of human health is a vital first step in streamlining processes and improving workflows.

Regulatory Reform Outcomes and Accelerated Regulatory Pathways for New Prescription Medicines in Australia.

National Regulatory Authorities (NRAs) globally are facing the challenge of evaluating pharmaceutical products in a speedy manner, whilst simultaneously ensuring adequate efficacy, safety and quality of approved products. Additionally, common expectations include that the evaluation process is competent, flexible, commensurate with risk, efficient and rapid. In 2014, the Australian regulatory system was out of step with global regulatory developments which led to a comprehensive regulatory review and reform process. As part of the reforms, two Facilitated Regulatory Pathways (FRP) were developed for prescription medicines: Priority Review (PR) and Provisional Approval (PA). Furthermore, regulatory reliance and recognition arrangements have been expanded with the Therapeutic Goods Administration (TGA) making increased use of evaluation reports by trusted NRAs. The new pathways have been utilised by the pharmaceutical industry in Australia since 2017, with the number of medicines going through these pathways gradually increasing. Additional facilitated pathways have been developed following the review, providing alternatives to the standard pathway for registration of prescription medicines in Australia. The reform is timely, helping to position Australia well in the current global regulatory climate.

A Critical Comparison of Comparators Used to Demonstrate Credibility of Physics-Based Numerical Spine Models.

The ability of new medical devices and technology to demonstrate safety and effectiveness, and consequently acquire regulatory approval, has been dependent on benchtop, in vitro, and in vivo evidence and experimentation. Regulatory agencies have recently begun accepting computational models and simulations as credible evidence for virtual clinical trials and medical device development. However, it is crucial that any computational model undergo rigorous verification and validation activities to attain credibility for its context of use before it can be accepted for regulatory submission. Several recently published numerical models of the human spine were considered for their implementation of various comparators as a means of model validation. The comparators used in each published model were examined and classified as either an engineering or natural comparator. Further, a method of scoring the comparators was developed based on guidelines from ASME V&V40 and the draft guidance from the US FDA, and used to evaluate the pertinence of each comparator in model validation. Thus, this review article aimed to score the various comparators used to validate numerical models of the spine in order to examine the comparator's ability to lend credibility towards computational models of the spine for specific contexts of use.

Identifying the Question Similarity of Regulatory Documents in the Pharmaceutical Industry by Using the Recognizing Question Entailment System: Evaluation Study.

BACKGROUND: The regulatory affairs (RA) division in a pharmaceutical establishment is the point of contact between regulatory authorities and pharmaceutical companies. They are delegated the crucial and strenuous task of extracting and summarizing relevant information in the most meticulous manner from various search systems. An artificial intelligence (AI)-based intelligent search system that can significantly bring down the manual efforts in the existing processes of the RA department while maintaining and improving the quality of final outcomes is desirable. We proposed a "frequently asked questions" component and its utility in an AI-based intelligent search system in this paper. The scenario is further complicated by the lack of publicly available relevant data sets in the RA domain to train the machine learning models that can facilitate cognitive search systems for regulatory authorities. OBJECTIVE: In this study, we aimed to use AI-based intelligent computational models to automatically recognize semantically similar question pairs in the RA domain and evaluate the Recognizing Question Entailment-based system. METHODS: We used transfer learning techniques and experimented with transformer-based models pretrained on corpora collected from different resources, such as Bidirectional Encoder Representations from Transformers (BERT), Clinical BERT, BioBERT, and BlueBERT. We used a manually labeled data set that contained 150 question pairs in the pharmaceutical regulatory domain to evaluate the performance of our model. RESULTS: The Clinical BERT model performed better than other domain-specific BERT-based models in identifying question similarity from the RA domain. The BERT model had the best ability to learn domain-specific knowledge with transfer learning, which reached the best performance when fine-tuned with sufficient clinical domain question pairs. The top-performing model achieved an accuracy of 90.66% on the test set. CONCLUSIONS: This study demonstrates the possibility of using pretrained language models to recognize question similarity in the pharmaceutical regulatory domain. Transformer-based models that are pretrained on clinical notes perform better than models pretrained on biomedical text in recognizing the question's semantic similarity in this domain. We also discuss the challenges of using data augmentation techniques to address the lack of relevant data in this domain. The results of our experiment indicated that increasing the number of training samples using back translation and entity replacement did not enhance the model's performance. This lack of improvement may be attributed to the intricate and specialized nature of texts in the regulatory domain. Our work provides the foundation for further studies that apply state-of-the-art linguistic models to regulatory documents in the pharmaceutical industry.

Mapeamento de processo regulatório para aprovação de vacinas novas provenientes de desenvolvimento nacional

The availability of medicines to the population necessarily goes through a long regulatory path, where several steps must be fulfilled. In this scenario, ANVISA is the national regulatory agency responsible for establishing the regulations that companies, producers and developers must follow. The objective of this work is to map the different regulatory processes involved in the approval of a vaccine, a type of biological medicine, developed by companies or national research institutions. Therefore, there is a focus on local regulations that involves the regulatory approval of a vaccine. The steps from the initial stages of development of a vaccine are accompanied by processes that are guided by regulatory requirements, often complex and with different directions. Until final release to the public, the rules governing this release involve several approvals that must be strictly followed by developers. Thus, the scope of this work is to delineate the regulatory processes from the initial stages of development of a vaccine, through the distinct phases of clinical trials, to its final approval for distribution to the general public, contributing to a global comprehension by researchers of the regulatory process as a whole.

A disponibilização de medicamentos à população passa necessariamente por um longo caminho regulatório, onde várias etapas devem ser cumpridas. Neste cenário, a ANVISA é o órgão responsável pelo estabelecimento da regulamentação que as empresas, produtores e desenvolvedores devem seguir. O objetivo deste trabalho é mapear os diversos processos regulatórios envolvidos na aprovação de uma vacina, que é um tipo de medicamento biológico, desenvolvido por empresas ou instituições de pesquisa nacionais. Desta forma, foca-se na regulamentação local que envolve a aprovação regulatória de um produto biológico. Os passos desde as etapas iniciais de desenvolvimento de uma vacina são acompanhados de processos que são norteados por requisitos regulatórios, muitas vezes complexos e envolvendo diferentes direcionamentos. Até a disponibilização final ao público, as normativas que determinam essa liberação envolvem diversas aprovações que devem ser rigorosamente seguidas pelos desenvolvedores. Desta forma, o escopo deste trabalho é delinear os processos regulatórios desde as fases iniciais de desenvolvimento de uma vacina, passando pelas diferentes fases de ensaios clínicos, até a sua aprovação final para a disponibilização à população, contribuindo para fornecer uma compreensão global aos pesquisadores do processo regulatório como um todo.