The Modern Merits of South Koreas Biopharmaceutical Industry
Bibliographic record
Abstract
The overview: In recent years, the South Korean economy has evolved from light goods, to heavy industry, to high tech and biotech. Along the way, the country has built a thoroughly modern legal and regulatory framework, an arguably world class educational infrastructure, and an unusually productive level of public-private partnership activity. How did it get here?: Migrating from a heavy manufacturing economy in the aftermath of the Korean War, South Korea began turning its attention to biopharmaceuticals as an opportunity to leverage the country’s increasing R&D and innovation capabilities, while relieving pressure to meet the healthcare needs and demands of an increasingly mature population. In 1994, the government launched the first national initiative to grow the industry-the “Biotech 2000” plan, investing roughly $20 billion for various biotech-related research initiatives from 1994 to 2000. This was followed by a second government-supported plan dubbed “Bio-Vision 2016,” a ten-year initiative with the goal of making South Korea one of the leading hubs of the biotech industry by 2016. The past decade has witnessed the formation of several key collaborations between South Korean companies and multi-national biopharma firms. Pfizer, AstraZeneca, Bristol-Myers Squibb, Sanofi, Novartis, and Otsuka have all invested heavily in local research and development. What’s the outcome?: As of 2012, South Korea’s top 20 biopharma companies (ranked by 2012 revenue) now total $6,978,110,000. According to the Bloomberg Global Innovation Index, South Korea ranks #1 in the world as the most innovative country in 2015 when considering a variety of metrics such as R&D capacity, productivity, and patent activity. The country’s annual R&D spending totals more than 4 percent of GDP (Source: The World Bank). To support the company’s rapid growth, Samsung announced plans in 2015 to build two more biologics manufacturing plants, at a cost of roughly $1.5 billion, to make the nation one of the largest biologics manufacturers worldwide. Samsung Bioepis is also planning a US IPO in 2016. According to a 2014 IMS report, South Korea’s biopharmaceutical industry is currently ranked fifteenth in the world, and is categorized alongside the United States, the EU5 nations, Japan, and Canada. From these actions, South Korea now ranks among the leading nations on other development indicators such as healthcare, education and R&D expenditure. South Korean life expectancy is now higher than the OECD average at 81 years old.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".