The evolving role of medical affairs in the pharma industry: a paradox perspective
Bibliographic record
Abstract
Purpose: The purpose of this work is to answer the following research question: how do changes in the scope of a job role confront its occupants with paradoxical challenges? With this in mind, I use the specific example of the medical role in the pharma industry, and provide a deeper understanding of how this function works, the several paradoxes medical face and predict what would be the best approach to manage these and the set of skills to develop in order to do so. Method: All the heads of medical in the region of Europe and Canada of a pharma biotech organization were interviewed (seven) and then applied inductive research and the systematic approach by Gioia, Corley and Hamilton (2012). Findings: For medical to succeed and become a primary strategic pillar in a pharma organization they should excel in transcendence and invest as core skills in project management, business acumen and clear communication, together with the already present scientific expertise. Originality/value: This study aims to explore how a change in a role due to a heavily disrupted marketplace setting raises paradoxical questions using the example of Healthcare and proposing a model to succeed in it.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.083 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".