The Working Patent and Pharmaceutical Industry Development in Indonesia
Bibliographic record
Abstract
Regulations regarding the working of pharmaceutical patents are intended to encourage invention, innovation, investment and transfer of technology.The fact is that the pharmaceutical industry is more interested in producing generic drugs than producing research drugs.The main objective to be achieved in this research is to answer predetermined problems, namely to explore and analyze the local working requirement policies, especially in the field of pharmaceutical patents linked to pharmaceutical industry development policies in order to fulfill drug availability for the public.By using analytical descriptive analysis, the findings the Indonesian pharmaceutical industry has not been able to achieve new drug discovery because there are still many obstacles, especially from the investment aspect.The national pharmaceutical industry has more interests in meeting market demand for pharmaceutical products in the context of the availability of drugs needed by the public.The development of of the pharmaceutical industry and medicinal raw materials in Indonesia is mainly constrained by technology and human resource capabilities.synthetic products produced is a lack of support from the upstream chemical industry.Potential opportunities for the development of biotechnology-based medicinal raw materials, by utilizing the wealth of biodiversity in Indonesia which is a potential resource in the pharmaceutical sector.The diversity of plants, microorganisms and marine biota is directly correlated with chemical diversity which has enormous potential for drug development.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".