The CAMCCO-L platform aims to provide training in English and French that complements the disciplinary academic training offered in universities by creating a virtual training environment that supports the development of skills essential to translational and transectorial research as well as interdisciplinary collaboration in perinatal research on medications.
CAMCCO-L is a new transdisciplinary virtual learning model offered at no cost that will help develop leaders in perinatal research on medications who will be then able to meet the complex interdisciplinary challenges of the current environment of this field of research.
As part of the CAMCCO-L training, selected trainees will also have the opportunity to participate in a Summer School on Drug Development and complete a research internship.
None, this track is open to all who wish to further their interdisciplinary knowledge and expertise in perinatal research on medications.
None, this track allows you to benefit from the CAMCCO-L training without commitment or obligation.
The internship and Summer School are optional steps in the 1-year curriculum.
or
and
Formal academic supervision by a CAMCCO-L mentor throughout the track
Mandatory enrollment in the Overarching Principles Module and at least 2 other modules complementary to the university training field
• Webinars
• Journal Clubs
Online courses offered on CAMCCO-L will be given live weekly (synchronous) via the CAMCCO-L Member Area.
After each course, the presentations and recordings of the majority of courses will be accessible in the archives of the CAMCCO-L Member Area to those registered for the courses.
Depending on the teaching language, a translation by subtitles in English or French will be offered for the recordings of all archived courses.
It will be possible to take the courses in any specific order, however, courses in some modules may be prerequisites for subsequent courses in the module.
To access the archived material of a course, you must have registered for the course in your Member Area.
Presenter: Anick Bérard
Presenter: Anick Bérardlink
Teaching Language: English
This course will present all the basic definitions, and overarching concepts and principles in perinatal pharmacoepidemiology. This will be given as a formal lecture with time for questions at the end.
Define all basic terminology used in perinatal pharmacoepidemiology, i.e., gestational age, prematurity, low birth weight, gestational diabetes and hypertension, pre-eclampsia and eclampsia, Apgar score, malformations, etc.
Definition and importance of organogenesis
Medication exposure time-windows of interest for important adverse pregnancy outcomes
Presenter: Anaïs Lacasse
Presenter: Anaïs Lacasselink
Teaching Language: French
This course will outline importance and methodological considerations surrounding the integration of sex and gender in pharmacoepidemiology through lectures, group discussions and examples drawn from the medical literature.
Understand the importance of integrating sex and gender in pharmacoepidemiology
Overview the different options for measuring sex and gender in existing databases studies or in the context of prospective data collection
Know best practices in terms of sex- and gender-based statistical analysis
Presenters: Andrea Triccolink; Kristi McIntosh and Amanda Doherty-Kirby (patient partners)
Teaching Language: English
This course will explore how to engage patients and public partners and knowledge users in research going through the main steps and elements to consider for co-creation of research with patients and other partners. This course will be presented in collaboration with two patient partners involved in perinatal research.
How to identify and engage with patients and public partners in research
Appreciation and conflicts of interest policies for patients and public partners in research
Capacity-building/training for patients and public partners in research
Evaluating and reporting patient and public engagement in research
How to consider ethics and equity, diversity, and inclusion in research
How to embed equity, diversity, and inclusion in the research process
Lessons learned and resources available on patient and public engagement in research
Presenter: Tania Saba
Presenter: Tania Sabalink
Teaching Language: English
Understanding the concepts behind equity, diversity and inclusion (EDI) is fundamental to achieving EDI goals and taking a more proactive approach to ensuring that different demographics are better represented in society at large. Addressing the dynamics of EDI is becoming a must and requires a shift in the way we work and deliver health care. Developing an EDI plan that incorporates a vision, mission, concrete actions and evaluation measures is key. Adopting and implementing a scientific and reasoned approach to EDI becomes essential for students, faculty, and health care providers to prevent discriminatory bias against people with different backgrounds and characteristics. By being more aware of our beliefs, committing to change our environment, and taking action, we will help individuals and organizations be more inclusive for those who work there and those who receive health care.
Gain a better understanding of the concepts of equity, diversity, and inclusion and the various laws that frame it
Identify our implicit biases and how they can affect the way we provide health services
Identify the risks, blind spots and benefits of equity, diversity and inclusion
Reflect on action plans to integrate equity, diversity and inclusion into our practices
Presenter: Louise Winn
Presenter: Louise Winnlink
Teaching Language: English
This course is Part 1 of a series of two that will introduce trainees to the basic principles of drug discovery and development. In this Part 1, an overview of a pharmacologic product from drug discovery to full development will be covered followed by a focus on target identification, drug design and synthesis, and efficacy determination.
Understand the critical role of basic science research in drug discovery
Articulate the principles of pre-clinical pharmacology studies
Describe how the components of ADME studies are assessed
Summarize how the principles of drug discovery are used to select appropriate lead candidates
Presenter: Louise Winn
Presenter: Louise Winnlink
Teaching Language: English
This course is Part 2 of a series of two that will introduce trainees to the basic principles of drug discovery and development. In this Part 2, a very brief overview of a pharmacologic product from drug discovery to full development will be reviewed, followed by a focus on required toxicology studies, and clinical trials.
Describe the principles of preclinical studies and how they support clinical trials
Articulate the types of toxicology studies needed with respect to drug development
Compare and contrast the study design of different types of clinical trials
Discuss the issues involved in drug discovery and development as they pertain to the use of medications in pregnancy
Presenter: Bruno Giros
Presenter: Bruno Giroslink
Teaching Language: English
In this course, basis for neuropharmacology will be covered and we will have an overview of the cellular and molecular brain, to understand why receptors and transporters represent more than 50% of all therapeutical targets and what are the future directions.
At the end of this course, trainees will be able to understand:
Brain cells and organization
Neurotransmitters
Anatomy
Metabotropic and ionotropic and receptors and their characterization
Plasmic transporters
Vesicular transporters
Presenter: Bruno Giros
Presenter: Bruno Giroslink
Teaching Language: English
Since 10-15 years, reverse pharmacology and the use of state of the art molecular tools allowed to decipher the role and function of any given protein and to deconstruct brain circuitry organization in complex behavior.
At the end of this course, trainees will be able to understand:
Transgenesis
Homologous recombination
Optogenetics
Chemogenetics
CRISPR/Cas 9
Presenter: Bruno Giros
Presenter: Bruno Giroslink
Présentateur : Bruno Giros
Teaching Language: English
No archived video recordings for journal clubs
This journal club aims to deepen critical appraisal skills and develop critical thinking for analyzing and reading scientific articles as it pertains to the study of adverse effects of environmental perturbations on behavior in animal models (in vivo). This session will provide an interactive and social opportunity for peer-to-peer learning, with time for questions and group discussion.
Additional Information
Trainees in our 2024-2025 cohort will be divided into 2 groups, and each group will present a review of one of the following articles during the journal club.
✓ Mourlon V et al. Maternal deprivation induces depressive-like behaviours only in female rats. DOI
✓ Baudin A et al. Maternal deprivation induces deficits in temporal memory and cognitive flexibility and exaggerates synaptic plasticity in the rat medial prefrontal cortex. DOI
Develop critical appraisal skills for analyzing and reading scientific articles
Identify and analyze the main methodological strengths and weaknesses of scientific articles
Develop collaborative and teamwork skills with respect to discussions surrounding scientific articles
Demonstrate enhanced presentation skills with respect to summarizing scientific articles
Presenter: Bruce Carleton
Presenter: Bruce Carletonlink
Teaching Language: English
This course will cover basic pharmacogenomic terminology, research methods and key limitations of these studies.
Pre-readings
✓ Blumenfeld YJ et al. Maternal-fetal and neonatal pharmacogenomics: a review of current literature. DOI
✓ Crisafulli C et al. Pharmacogenetic and pharmacogenomic discovery strategies. DOI
Define basic terminology used in pharmacogenomic studies
Describe pharmacogenomic research methods used in discovery research
Identify key limitations in pharmacogenomic research
Understand why genetics matters in perinatal pharmacoepidemiology and drug outcome studies
Presenter: Bruce Carleton
Presenter: Bruce Carletonlink
Teaching Language: English
This course will summarize value and limitations of Big and Small data drug outcome studies and why both study types improve the rigour of each other.
Pre-readings
✓ Bissel M. Reproducibility: The risks of the replication drive. DOI
✓ Allison DB & Fineberg HV. EPA's proposed transparency rule: Factors to consider, many; planets to live on, one. DOI
Summarize the value and limitations of Big Data drug outcome studies
Summarize the value and limitations of Small Data drug outcome studies
Appraise the value of both study designs examining the same outcome
Presenter: Bruce Carleton
Presenter: Bruce Carletonlink
Teaching Language: English
This course will explore key methods of implementation science in both perinatal epidemiology and pharmacogenomic studies and will have participants designing implementation science methods for a perinatal pharmacogenomic study.
Pre-reading
✓ Phillips CA et al. Implementation science in pediatric oncology: A narrative review and future directions. DOI
Describe key methods of implementation science in perinatal epidemiology studies
Describe key methods of implementation science in pharmacogenomic studies
Design implementation science methods for a perinatal pharmacogenomic study
Presenter: Bruce Carleton
Presenter: Bruce Carletonlink
Teaching Language: English
This course will describe key thresholds for evidence-based pharmacogenetic testing as well as limitations and value of commercial panels.
List three key thresholds for the use of evidence for clinical pharmacogenetic testing
Describe key limitations of commercial pharmacogenetic testing panels
Determine the value of pharmacogenetic testing from clinical examples
Presenter: Bruce Carleton
Presenter: Bruce Carletonlink
Teaching Language: English
No archived video recordings for journal clubs
This course will evaluate the quality of a perinatal outcome study and appraise the value of a fetal pharmacogenomic study. The use of both study types in succession will be discussed.
Additional Information
Trainees in our 2024-2025 cohort will be divided into 2 groups, and each group will present a review of one of the following articles during the journal club.
✓ Moriello C et al. Off-label postpartum use of domperidone in Canada: a multidatabase cohort study. DOI
✓ Raymond M et al. Fetal pharmacogenomics: A promising addition to complex neonatal care. DOI
Evaluate the quality of a perinatal outcome study
Appraise the value of a fetal pharmacogenomics study
Interpret the value of using pharmacoepidemiology and pharmacogenomic methods examining the same outcome
Presenter: Sherif Eltonsy
Presenter: Sherif Eltonsylink
Teaching Language: English
This course will introduce trainees to basic pharmacoepidemiology principles and concepts, including study designs and their basic features. The course will also provide an understanding of bias and confounding in pharmacoepidemiology.
Introduce the basic principles, concepts, and study designs in pharmacoepidemiology
Provide an overview of the basic features of cohort and case-control designs
Provide an introduction of bias and confounding in pharmacoepidemiology
Explore how bias and confounding are introduced, and how they can be avoided or controlled
Presenters: Brandace Winquistlink and Anick Bérardlink
Teaching Language: English
This course will explore common data sources used in pharmacoepidemiology and methodological considerations through didactic lectures, group discussions, and examples from the medical literature.
Introduce the concept of real-world data in the context of perinatal pharmacoepidemiology
Provide an overview of common data sources and pregnancy cohorts
Review coding classification systems and data definitions
Explore harmonization of data models across jurisdictions and quality considerations in data linkage
Validation studies done using the Quebec Pregnancy Cohort
Presenters: Gillian Hanleylink and Azar Mehrabadilink
Teaching Language: English
This intermediate phamacoepidemiology course will build upon the introductory course and present methods used to correct for confounding, including propensity score matching, instrumental variables, time-varying exposures in pregnancy, etc. This will be given as a formal lecture with question periods built in and some breakout group work.
Review common sources of bias in pharmacoepidemiologic studies during pregnancy, immortal time bias, and selection bias (e.g. left-truncation bias)
Introduce methods for addressing these sources of bias, including, but not limited to propensity score matching, instrumental variables, time-varying exposures, etc.
Discuss study designs that reduce the risk of these sources of bias
Presenters: Gillian Hanleylink and Azar Mehrabadilink
Teaching Language: English
This follow-up course to Part 1 of intermediate pharmacoepidemiology will introduce quasi-experimental methods that can be used to better target causal research questions. This will be given as a formal lecture with question periods built in and some breakout group work.
Introduce the role of quasi-experimental designs in pharmacoepidemiology
Cover some novel uses of quasi-experimental designs to address important perinatal epidemiology research questions
Outline some useful quasi-experimental designs for pharmacoepidemiology research in pregnancy, including, but not limited to regression discontinuity design, interrupted time series, etc.
Presenter: Anick Bérard
Presenter: Anick Bérardlink
Teaching Language: English
No archived video recordings for journal clubs
This course will use published manuscripts to review and summarize all concepts seen within the Pharmacoepidemiology Module. This session will be interactive with questions and answers.
Additional Information
Trainees in our 2024-2025 cohort will be divided into 2 groups, and each group will present a review of one of the following articles during the journal club.
✓ Cleary B et al. Methadone, Pierre Robin sequence and other congenital anomalies: case–control study. DOI
✓ Andersen SL et al. Maternal Thyroid Function, Use of Antithyroid Drugs in Early Pregnancy, and Birth Defects. DOI
Develop critical appraisal skills for analyzing and reading scientific articles
Identify and analyze the main methodological strengths and weaknesses of scientific articles
Develop collaborative and teamwork skills with respect to discussions surrounding scientific articles
Demonstrate enhanced presentation skills with respect to summarizing scientific articles
Presenter: Steven Hawken
Presenter: Steven Hawkenlink
Teaching Language: English
This course will target statisticians, epidemiologists, data scientists and other quantitative researchers/students with a basic familiarity with regression modeling. The course will cover general strategies for fitting prediction models for continuous, categorical and timeto-event outcomes, including: exploratory analysis/data visualization; missing data imputation; covariate selection; model specification; model validation/calibration; handling non-linearity; and choosing between conventional statistical models and machine learning models (and the differences between these types of models). Extensive use of R, RStudio and Frank Harrell’s Hmisc and rms r-packages will be used in the course material and casestudies/examples. The course will follow the general philosophy of Regression Modelling Strategies - 2nd Edition textbook by Frank Harrell (Optional, but recommended course textbook; all necessary readings/lecture notes will be provided for participants).
Methods for exploring, describing and understanding your data in preparation for regression modeling
Fitting multivariable regression models appropriate for continuous, categorical, and time to event outcomes
Address issues of sample size and overfitting
Approaches to addressing missing data
Handling complex non–linear or non–additive relationships
Testing/quantifying associations between one or more predictors and the response, and interpreting the fitted model
Model validation and calibration to evaluate predictive accuracy and identify overfitting
Learn the differences between machine learning and statistical models, and how to choose the best approach for a given problem
Presenter: Steven Hawken
Presenter: Steven Hawkenlink
Teaching Language: English
This course will target statisticians, epidemiologists, data scientists and other quantitative researchers/students with a basic familiarity with regression modeling. The course will cover general strategies for fitting prediction models for continuous, categorical and timeto-event outcomes, including: exploratory analysis/data visualization; missing data imputation; covariate selection; model specification; model validation/calibration; handling non-linearity; and choosing between conventional statistical models and machine learning models (and the differences between these types of models). Extensive use of R, RStudio and Frank Harrell’s Hmisc and rms r-packages will be used in the course material and casestudies/examples. The course will follow the general philosophy of Regression Modelling Strategies - 2nd Edition textbook by Frank Harrell (Optional, but recommended course textbook; all necessary readings/lecture notes will be provided for participants).
Methods for exploring, describing and understanding your data in preparation for regression modeling
Fitting multivariable regression models appropriate for continuous, categorical, and time to event outcomes
Address issues of sample size and overfitting
Approaches to addressing missing data
Handling complex non–linear or non–additive relationships
Testing/quantifying associations between one or more predictors and the response, and interpreting the fitted model
Model validation and calibration to evaluate predictive accuracy and identify overfitting
Learn the differences between machine learning and statistical models, and how to choose the best approach for a given problem
Presenters: Michal Abrahamowiczlink and Marie-Eve Beauchamp
Teaching Language: English
This, relatively advanced, course in applied biostatistics is designed for graduate trainees and researchers in (bio-)statistics, (pharmaco-)epidemiology, data science, as well as public health, who have good understanding of multivariable regression and some knowledge of applied survival analysis (especially of the Cox model).
The 1st part will focus on the non-technical conceptual introduction to relevant statistical modeling methods and real-life applications (mostly in pharmacoepidemiology), with an overview of different modeling approaches that may be considered to analyze associations between a time-varying drug exposure and time to a clinical endpoint (e.g., an adverse event or death). Then, the importance of considering potential (i) latency between exposure and change in risk and/or (ii) cumulative effects of past exposures will be discussed. Next, the Weighted Cumulative Exposure (WCE) methodology will be explained in a way accessible for participants without formal background in statistics or biostatistics.
The 2nd part will focus on practical issues related to the use of the R package WCE to analyze real-world pharmacoepidemiology data. The way data have to be prepared for WCE analyses and the steps necessary to carry out these analyses will be explained.
To understand the methodological challenges related to the time-varying aspects (within-subject & between-subjects variation in timing, dosage and duration of drug use), of drug exposure in real-world pharmacoepidemiology research, and its potential cumulative effects
Get a ''non-technical'' conceptual overview of the rationale and general features of flexible statistical modeling of cumulative effects
To illustrate the practical usefulness of the methods introduced in the previous learning objective, and the new insights offered by these methods, through 3 specific real-world examples, involving safety (adverse effects) or effectiveness of particular drugs
To get practical instructions regarding the use of the software that implements the methods introduced and illustrated in previous learning objectives
Presenter: Christopher Gravel
Presenter: Christopher Gravellink
Teaching Language: English
This course will discuss the fundamentals for applying propensity score methods in observational research with a focus on pharmacoepidemiology. We will cover the basic principles behind causal inference concepts and motivate their use for reducing the impact of confounding due to observed covariates. The emphasis of the course will be on the practical application of these methods using examples in the R programming language and will focus specifically on matching and inverse probability of treatment weighting. Strategies to address common complications in propensity score analyses will be discussed.
Understand the principles underlying inferring causal effects in observational data
Understand the concept of directed acyclic graphs (DAGs) and confounding
Obtain a conceptual understanding of propensity score analysis and the circumstances under which they may be used
Using R based examples, learn how to implement propensity score matching and inverse probability of treatment weighting
Understand how to compute and diagnostics and interpret the findings of propensity score analyses
Presenters: Andrea Triccolink and Areti Angeliki Veroniki
Teaching Language: English
Part 1 of this course will explore how to engage with knowledge users in research by covering different types of knowledge synthesis methods for decision-making. The main steps and elements to consider for co-creation of research with knowledge users will be discussed.
Describe co-creation and why it is important in research
Identify knowledge users who can be engaged in research
Identify different types of knowledge synthesis for decision-making (systematic review, meta-analysis, network meta-analysis, scoping reviews, overview of reviews, rapid reviews)
Describe how to select a knowledge synthesis method for a particular research question
Presenters: Andrea Triccolink and Areti Angeliki Veroniki
Teaching Language: English
Part 2 of this course will explore important topics in evidence synthesis, building on their previous introductory training on knowledge synthesis. Attendees will be introduced to the basic principles and concepts of network meta-analysis (NMA). The key assumptions of NMA, including transitivity and consistency between different sources of evidence in a network will be exemplified.
Demonstrate the basic principles of pairwise meta-analysis
Identify effect measures used in meta-analysis for dichotomous and continuous outcomes
Introduce heterogeneity, and common meta-analytical approaches (common and random effects models)
Describe important aspects of interpreting meta-analysis results using real-life examples
Understand the usefulness of NMA in medical research
Communicate how direct and indirect evidence can be combined within NMA and how it is related to pairwise meta-analysis
Understand principles and prerequisite assumptions in NMA, and investigate heterogeneity, intransitivity, and inconsistency
Understand and present different methods for ranking interventions
Become familiar with ways of presenting the results of network meta-analysis
Presenter: Marc Lanovaz
Presenter: Marc Lanovazlink
Teaching Language: English
This course involves an introduction to the use of machine learning in applied research. Specifically, the instructor will review the assumptions and concepts underlying the application of machine learning to conduct research with health and behavioral data.
Define machine learning and basic related concepts
Describe, in words the general functioning of at least one machine learning algorithm
Explain the logic underlying the research methodology used in machine learning
Identify research questions that can be investigated using machine learning
Presenter: Padma Kaul
Presenter: Padma Kaullink
Teaching Language: English
This course will showcase examples of how artifical intelligence (AI) and machine learning (ML) methods are being used in perinatal research. The instructor will discuss AI-ML methods, common challenges, and solutions. The attendees will get exposure to several examples from published and ongoing research projects within the Canadian Mother-Child Cohort (CAMCCO) that utilize AI-ML methodology.
Become familiar with commonly used AI-ML methodologies in perinatal research
Identify strengths and limitations and common challenges of using AI-ML in perinatal research
Understand the steps involved in designing an AI-ML study
Presenter: Mark Walkerlink
Presenter: Kevin Dick
Teaching Language: English
Presenter: Serge McGraw
Teaching Language: English
This workshop will introduce trainees (MSc, PhD and postdocs) on how to organize and write fellowship applications. Trainees will learn what are the common mistakes observed during the reviewing process and how we can avoid them. This workshop will concentrate on Canadian Institutes of Health Research (CIHR) awards, but the ideas will apply to the majority of fellowships.
Dr. Serge McGraw is an Associate Professor in the Department of Obstetrics and Gynecology at the University of Montreal. His principal research interests are focused on the harmful developmental outcomes caused by epigenetic instabilities arising from alterations in DNA methylation profiles during early embryogenesis. By combining in vitro stem cell models as well as in vivo mouse models with multi-omics sequencing approaches, his laboratory aims at understanding how perturbations in the early embryonic program may lead to epigenetics errors driving in the occurrence of prenatal or after birth developmental disorders.
Presenter: Jessica Gorgui
Teaching Language: English
This webinar will explore the critical role of pharmacovigilance in monitoring drug safety, with a focus on isotretinoin, a treatment for severe acne, and particularly in the context of pregnancy. Different practices in the USA, Canada and Europe will be compared.
Dr. Jessica Gorgui (PhD) holds a Bachelor’s degree in Biomedical Sciences (2012), a Master’s degree in Clinical Pharmacology (2015) and a doctorate in Pharmacoepidemiology (2023) from the University of Montreal. She has been the pharmacoepidemiologist at the Medication and Pregnancy Research Unit (Dr. Anick Bérard) since 2021. Dr. Gorgui is now also the Scientific Director of the newest initiative of CAMCCO, the populational pregnancy registry while continuing to be involved in CAMCCO-Learn (Advisory Committee) and CAMCCO-Outreach (Co-Investigator, Scientific Content Reviewer). She is also a lecturer at the University of Montreal, both at the undergraduate and graduate levels where she teaches epidemiology methods and pharmacovigilance.
Presenter: Kenji Momo
Teaching Language: English
This webinar will introduce (1) a Japanese database available for pharmacoepidemiological research, and (2) researches using the dataset. Audiences will learn what is the Japanese database via actual research results obtained using the dataset for future research collaboration.
Dr. Kenji Momo (PhD and Pharmacist) is an Associate Professor at the School of Pharmacy, Showa University (Japan). He studied data analysis for kidney disease in Karolinska Institute (Stockholm, Sweden) from 2022 to 2023. His principal research interests are focused on pharmacoepidemiology and drug development using medical big data. He covered not only children and pregnancies, but also kidney disease, cancer and cardiovascular diseases for relating drug harm.
Presenter: Takoua Boukhris (Epidemiologist, Health Canada)
Teaching Language: English
This webinar will provide you insights on career development in Canada’s public service environment with regards to post-market regulation of pharmaceutical drugs as well as vaccination surveillance and monitoring systems.
During this webinar, key information to be conveyed includes:
✓ Tangible actions you can take to navigate and grow your career in the public service, especially vaccination surveillance and monitoring;
✓ Career growth mindset, factoring in fulsome career development approach in the field of epidemiology from regulation towards to surveillance and monitoring, with concrete example(s) from personal experience within Public Health sector portfolio;
✓ Supports available to you to help you plan, prepare, and take career action steps tailored to your career expectations.
Takoua Boukhris was trained in pharmacoepidemiology at the University of Montreal. She holds a PhD degree in Pharmaceutical Sciences – Option Medications and Population Health. Moreover, she obtained a MSc in Microbiology and Immunology from the University of Montreal. She is an Epidemiologist, starting her career with Health Canada within the Health Products and Food Branch. Takoua brings over 5 years of experience in post-market drug regulation and vaccine surveillance within the federal government (Health Canada and Public Health Agency of Canada) to inform policy development and guide public education and awareness initiatives.
Biography Coming Soon!
Presenter: Maxim Lemelin (Market Access Manager, Pfizer Canada – Oncology)
Teaching Language: English
Biography Coming Soon!
Presenter: Natalie Dayan
Teaching Language: English
In this webinar, we will review historical events and bioethical issues that have led to the systematic exclusion of pregnant and lactating people in clinical trials and discuss challenges to studying these populations, and strategies to overcome them.
Dr. Natalie Dayan (MD, MSc) is an Associate Professor of Medicine at McGill University and a General Internal Medicine specialist at the McGill University Health Centre (MUHC) where she leads the Obstetric Medicine clinical service and training program. She is a Scientist at the Clinical Outcomes Research and Evaluation, Research Institute of the MUHC and holds the Fonds de recherche du Québec – Santé (FRQ-S) Chercheur Boursier Clinicien award (Junior 2) and an Early Career Professorship for Women’s Heart and Brain Health from McGill University and the Heart and Stroke Foundation of Canada. Her research work which is funded by Canadian Institutes of Health Research (CIHR) and the Heart and Stroke Foundation is clinical and epidemiological and focuses on maternal health outcomes after infertility treatment, long-term health outcomes and health service use after pregnancy complications, and the link between breastfeeding and postpartum blood pressure. Dr. Dayan has also developed and directs a formal mentorship program for the Department of Medicine at McGill University using a novel and innovative software solution, based on best practices in academic mentorship and focused on the needs of early career academics. Dr. Dayan strives to build capacity through not only scientific rigor but also brings a holistic approach to mentorship and training that takes into account all aspects of academic life.
Biography Coming Soon!
Presenter: Christopher Gravel
Teaching Language: English
This webinar will introduce spontaneous reporting (SR) databases and discuss how they fit into pharmacovigilance processes within the drug product lifecycle. Attendees will learn how to mine the FDA’s Adverse Event Reporting System (FAERS) database for drug safety hypothesis generation, or signal detection, using disproportionality analysis algorithms in R. The challenges in the interpretation of detected signals will be discussed, and the forms of bias specific to these analyses will be reviewed. Finally, some of the challenges in the practical use of SR data for drug safety surveillance will be overviewed, and potential ways to mitigate these concerns will be highlighted.
Dr. Gravel (PhD) is an Assistant Professor of Biostatistics in the School of Epidemiology and Public Health at the University of Ottawa. He obtained his MSc and PhD in Probability and Statistics from the School of Mathematics and Statistics at Carleton University followed by post-doctoral fellowship in the Department of Epidemiology, Biostatistics and Occupational Health at McGill University, where he is currently an Adjunct Professor. His research is on the development and improvement of methods for drug and vaccine safety studies with a particular focus on measurement error models, disproportionality analysis and causal inference. In addition, prior to joining the University of Ottawa, Dr. Gravel worked for Health Canada where he developed interests in the use of biostatistics for regulatory decision-making, and designed and taught a regular course the subject. He currently teaches advanced biostatistics for graduate students in the epidemiology program.
The next Summer School (SSM15) will take place in the summer of 2025 at the University of Montreal.
People wishing to apply for an internship within the Mitacs Accelerate Program can also apply for a Mitacs bursary.