Understanding purchasing patterns and product access of newly launched specialty generics
Bibliographic record
Abstract
Background: Many specialty drugs have lost patent exclusivity and more specialty generics (SGs) are expected in the future. Payers continue to look for ways to manage health care costs in the specialty pharmacy space and SG products offer the opportunity for savings. Given increasing interest in SGs, manufacturers are expected to invest more than $100 billion in the development of SGs over the next five years. To remain competitive, pharmacies must have access to SG products and access to competitive pricing for SGs, which can be obtained by accessing pharmaceutical manufacturer agreements through MHA Specialty Pharmacy Solutions. Aims: Understand purchase patterns of newly launched SGs and see if increased access to product was facilitated by the entrance of a SG. Methods: To determine purchase patterns of newly launched SGs, the rate of change of both the brand and generic products were measured for five specialty drugs across MHA pharmacy members. When possible, the brand rate was measured by the units of brand product purchased the quarter prior to the generic launch compared to the number of units in first quarter 2019 (1Q19). The generic product rate was measured by the units of generic product in the quarter it launched compared to units in 1Q19. To detect changes in product access to SGs, the number of corporations dispensing the brand was measured in the quarter prior to the generic launch compared with the number of corporations dispensing the generic in 1Q19. Results: Brand imatinib (Gleevec1) number of units decreased 80% while generic imatinib units grew by 134%. The number of corporations dispensing generic imatinib increased 34%. Brand hydroxyprogesterone caproate (OHPC) (Makena2) number of units decreased 67% while generic OHPC units grew by 641%. The number of corporations dispensing generic OHPC increased 38%. Brand abiraterone acetate (Zytiga3) number of units decreased 63% while generic abiraterone units grew by 289%. The number of corporations dispensing generic abiraterone increased 60%. Brand tetrabenazine (Xenazine4) and brand dalfampridine ER (Ampyra5) could not be measured due to limited distribution. Generic tetrabenazine units increased 2967% and the number of corporations dispensing increased 2114%. Generic dalfampridine ER units increased 1451% and the number of corporations dispensing increased 463%. Conclusions: Pharmacies purchasing through MHA Specialty Pharmacy Solutions are able to expand their access to products and quickly adopt SGs in order to grow their businesses and serve patients.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".