Personalized medicine hits primary practice as genetic testing is being done for the first time in family practice to better select psychiatric medications for patients: an interview with Dr. Nicholas Voudouris
Bibliographic record
Abstract
For the first time in Canada, genetic testing done at the Centre for Addiction and Mental Health (CAMH) in Toronto is being made available to family physicians. This leading-edge research started just over a year ago at the Thornhill Medical Centre in Thornhill, Ontario. The aim of the research is to use genetic testing to better select psychiatric drugs and dosages to improve efficacy and reduce side effects in patients suffering from mental illness. Dr. Nicholas Voudouris, a family physician at the Thornhill Medical Centre who is heavily involved in this project, describes it as leading-edge science that has the possibility of having profound impact on personalized medicine at the primary care level. I spoke with Dr. Voudouris to learn more about him, this project, and the future implications genetic testing could have on personalized medicine and reducing health care spending.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.012 | 0.048 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".