Role of a Medical Statistician
Medical Statisticians are key players in a drug development project team within the research, development and manufacturing of a pharmaceutical product.
Statisticians are becoming highly sought in the pharmaceutical industry and increasingly play leading roles in areas such as pharmacology, health economics, real world evidence, personalised healthcare, manufacturing and marketing.
Statisticians are involved in a wide range of activities, including:
- Designing scientifically sound experiments or trials
- Defining data collection methods
- Determining the analysis methodology and requirements
- Performing data analysis
- Correct interpretation and decision making
- Present results to senior managers and government agencies around the world
Statisticians almost never work in isolation in the pharmaceutical industry. Project teams are made up of a variety of disciplines, to include doctors, scientists, operations managers, compliance and marketing teams.
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Role of a Statistical Programmer
Many pharmaceutical companies and contract research organisations (CROs) employ statistical programmers who work closely with the statisticians to carry out a wide range of activities.
Their main role is to help design and then program the tables, listings and figures that summarise the data collected during a clinical trial. Statistical programmers are also responsible for developing and validating computer software and macros, both in-house and externally purchased, used by both statisticians and statistical programmers.
It is important that they are often searching for the most efficient techniques for statistical reporting and skills such as good algorithm design and defensive programming are important. Programmers also need to stay up-to-date with different software functionalities and tools so that programmers can easily adapt their existing knowledge to new programming environments and languages.
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Job Requirements
Each year the demand for qualified statisticians increases.
Medical statisticians almost always have an MSc in Statistics, and a PhD is not uncommon. The MSc courses are seen to provide a strong background in statistics as well as the ability and confidence to apply the knowledge to a wide range of problems.
expertise’s and to think strategically and make a wider contribution to the employer beyond a purely statistical input.
Employers look beyond educational background and seek a range of capabilities:
- Ability to work individually and within teams
- An eye for detail, well organised and a logical thinker
- Aptitude for programming. Companies typically use SAS, R, Python, STATA, SQL. Training will usually be provided to new starters.
- Confident communicator and presenter of statistical concepts to colleagues with non-statistical background
- Influence colleagues from other disciplines and to think strategically beyond the statistical analysis
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Job Prospects
Do you want a career that is exciting, varied, always advancing and makes a real difference to the lives of people all over the world?
Pharmaceutical research and development is changing fast and with it the roles of statisticians and statistical programmers are continually being re-defined. The historical ‘one-size fits all’ drug model is quickly being replaced by innovative, targeted, personalized medicine. The increasing pressure of government budget cuts and availability of biosimilars necessitates an alternative, more agile approach to drug development. The pharmaceutical industry is moving into a new era where analytical skills are highly sought: adaptive, flexible trial designs are replacing traditional phase I-IV models, interactive, dynamic data displays provide more flexibility and speed over traditional static reports.
The desire for personalized healthcare is leading the way to exploring high dimensional data such as imaging, genetics and biomarkers. New and exciting opportunities are opening in the field of big data and with-it techniques for artificial learning and machine learning.
For these reasons, the industry is turning to the following innovative approaches:
- Screening large numbers of candidate molecules for development using high power computing
- Furthering our understanding of the biology of diseased patients to help identify specific disease targets
- Systematic review (network meta-analyses and data-mining) of prior research together with newly available data
- Modelling and simulation based approaches which link information from pre-clinical animal studies and human clinical trials
- Bayesian statistics that allow prior information from existing knowledge to be used
- Flexible and efficient trial designs that seek to terminate ineffective drugs early on. Valuable resources can then be re-directed towards more promising drugs
- Close partnerships with academia, technology companies, patient advocate groups
- High dimensional data such as imaging, genetics and biomarker that require machine learning and artificial intelligence techniques
- Increased sharing and transparency of data
In almost all these areas, the role of statistics and statisticians is growing. Are you up for the challenge?
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