GCRI · Biotechnology and Biosecurity
Biotechnology platforms at Biotechnology and Biosecurity
How biotechnology platforms is applied in Biotechnology and Biosecurity. Biotechnology platforms apply biological systems to produce medicines, diagnostics, materials and agricultural products. They expand response capacity for health threats while introducing dual-use and biosafety concerns.
Biotechnology platforms at Biotechnology and Biosecurity on the record.
- MethodBiotechnology platforms
- StewardBiotechnology and Biosecurity
- Applied inBiotechnology and Biosecurity
- Data5 inputs
- ChecksValidation
- Canonical pageSTEM Commons
What biotechnology platforms does here.
Biotechnology platforms apply biological systems to produce medicines, diagnostics, materials and agricultural products. They expand response capacity for health threats while introducing dual-use and biosafety concerns. In health and biosecurity and food and agriculture, biotechnology capacity shapes how quickly countermeasures can be produced in a crisis. Its supply chains and dual-use potential are part of biosecurity planning. The canonical description is on the STEM Commons.
- 01
Methods used here
genetic engineering; bioprocess design; high-throughput screening; diagnostic assay development; vaccine platform development; biosafety risk assessment.
- 02
Validation
Products are evaluated through staged preclinical and clinical testing and manufacturing quality controls. Regulatory review and independent replication check claims.
SEIR on a network of places.
An outbreak seeded in one place spreads through a small-world network by the share of contacts people make elsewhere; play it to see the order of arrival and how the timing of measures moves the peak. Teaching model with stated illustrative values, not a prediction.
Controls
- Basic reproduction number R0
- 2.5
- Latent period
- 3.0 days
- Infectious period
- 5.0 days
- Share of contacts made in other places
- 8%
- Places in the network
- 24
- Measures start on day
- 40
- Contact reduction from measures
- 40%
- Days simulated
- 240 days
Readouts
- Peak new infections
- 3.97 per 1,000 a day
- Day of the peak
- 122
- Share ever infected
- 54%
- Places reached
- 100%
- Reproduction number under measures
- 1.50
Numbers, methods and sources
| Day | New infections per 1,000 | Cumulative infected (%) |
|---|---|---|
| 0 | 0.00 | 0.0 |
| 17 | 0.02 | 0.0 |
| 34 | 0.21 | 0.2 |
| 51 | 0.66 | 1.0 |
| 68 | 1.33 | 2.6 |
| 85 | 2.32 | 5.8 |
| 102 | 3.38 | 10.7 |
| 119 | 3.96 | 17.1 |
| 136 | 3.77 | 23.7 |
| 153 | 3.32 | 29.7 |
| 170 | 3.09 | 35.1 |
| 187 | 3.03 | 40.3 |
| 204 | 2.90 | 45.3 |
| 221 | 2.53 | 50.0 |
| 238 | 1.86 | 53.7 |
Methods
- SEIR compartments Kermack and McKendrick (1927), Proc. R. Soc. A 115
- Metapopulation coupling by mobility Balcan and others (2009), PNAS 106
- Small-world network Watts and Strogatz (1998), Nature 393
- Modelling infectious diseases Keeling and Rohani (2008), Princeton University Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Cities Natural Earth
- Airports Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Biotechnology and Biosecurity in Foundry
- Tested at Biotechnology and Biosecurity in Universe
- Codified in Health and Biosecurity in Standards
- Published in Biotechnology and Biosecurity in Reports
- Taught in Faculty of Health and Society in Academy
What the method consumes.
Datasets and records used by biotechnology platforms on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Laboratory automation systems | Input | OBSERVED |
| Bioreactor process data | Input | OBSERVED |
| Clinical trial registries | Input | OBSERVED |
| Genomic databases | Input | OBSERVED |
| Manufacturing quality records | Input | OBSERVED |
The model, the data and the uncertainty.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Uncertainty bands
How far the outlook for Biotechnology platforms at Biotechnology and Biosecurity could spread, shown as ranges rather than a single line.
- Central estimate
- median of the ensemble
- Ranges
- likely and very likely, in IPCC calibrated language
- Ensemble
- members, scenarios and initial conditions stated
- Read with
- the sensitivity of the result to each input
How results are checked.
Products are evaluated through staged preclinical and clinical testing and manufacturing quality controls. Regulatory review and independent replication check claims.
Scale-up from laboratory to production often fails or takes time. Containment and oversight can lag behind technical capability.
Topics that rely on this method.
Who maintains the method.
Biotechnology and Biosecurity stewards biotechnology platforms for the Consortium and reviews how it is applied across platforms.
Questions and answers.
What are the limits of biotechnology platforms in this field?
How are results checked?
Are the values on this page real?
Where else is this method applied?
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