Certification for Working Professionals
Take your career to the next level
As an experienced pharmaceutical professional, many find their careers stalled on single projects or routine tasks that have little to no change. The pharmaceutical industry is a challenging, dynamic environment with regulatory and clinical changes in every aspect of its operation. What you may have learned a decade ago has evolved while new regulations are emerging daily in areas that did not exist a few year ago.
How can a working professional keep up with the demands of this dynamic industry? It’s more than superficial awareness of the changes. In order to make a career move or advancement, you need to be more than simply informed; you need to be in charge and knowledgeable enough to execute the nuances. It’s knowledge and advanced skills that put you a step ahead of the competition. MMS Academy is your partner of choice when it comes to updating your pharmaceutical industry skills, or learning new skills and regulations. We are constantly at the forefront of evolving regulations and monitor the impact these changes have on the industry. Our experienced instructors are subject-matter experts with decades of pharmaceutical experience and are currently working with top-tier pharma and life science clients.
Whether your interest is improving your existing skills, or learning new methodologies, MMS Academy is your gateway to excellence in the pharmaceutical industry.
These courses are for the clinical and regulatory focused individuals in the pharmaceutical industry and allow you to apply your skills to almost any regulatory document.
These introductory courses walk the aspiring programmer through high-level concepts related to clinical programming in the life science industry.
In these unique courses, students will learn about the legal and ethical basis for trail disclosure and clinical trial protocols and results.
These courses offer entry level medical professionals the fundamentals of medical coding and its application in clinical trial data sets.