Skip to content

GCRI · Biotechnology and Biosecurity

Biomanufacturing

Biomanufacturing uses cells, enzymes and microorganisms to make products at scale: medicines and vaccines, food ingredients, chemicals and materials. It can reduce dependence on fossil feedstocks and shorten supply chains, but it brings its own process safety, quality and supply risks. This topic, studied at Biotechnology and Biosecurity, a platform of The Global Centre for Risk and Innovation (GCRI), examines industrial biology as a production system and the risks that come with scaling it up.

Make an enquiry Back to Topics
01Register

Biomanufacturing on the record.

Biotechnology and Biosecurity
  1. PublisherThe Global Centre for Risk and Innovation
  2. FieldHealth and biosecurity, Food and agriculture
02Core questions

What experts ask.

  • What limits the scale-up of biological processes from laboratory to factory?
  • How concentrated is production capacity for essential biological products?
  • How are contamination, containment and quality managed in large-scale production?
  • What environmental benefits and burdens does biomanufacturing carry across its life cycle?
  • How can surge capacity be organised for health emergencies?
03Geography

Environmental exposure in West Africa.

Daytime surface heat, population density and haze over West Africa, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Environmental exposure, for this page

About this layer
Evidence
Observed (persistent cloud still leaves gaps)
Source
VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
8-day; Satellite 8-day composite; persistent cloud still leaves gaps
Newest at build
2026-09-14
Resolution
about 1 km grid
Uncertainty
Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Estimated
Source
Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
Provider
NASA SEDAC (CIESIN, Columbia University)
Licence
CC BY 4.0
Vintage
null; Census-based estimate, static (2020)
Resolution
about 1 km grid
Uncertainty
Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds leave gaps)
Source
VIIRS NOAA-20 Deep Blue AOD (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite retrieval; clouds leave gaps
Newest at build
2026-10-14
Resolution
about 2 km grid
Uncertainty
Satellite measure of haze, smoke and dust through the whole air column on the day shown; an exposure indicator, not ground-level PM2.5, an air quality index or a health warning.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds leave gaps)
Source
MODIS Terra NDVI (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite index; clouds leave gaps
Newest at build
2026-10-13
Resolution
about 250 m grid
Uncertainty
Satellite greenness index over the 8 days to the date shown; an indicator of crop and pasture condition, not a yield estimate or a food security warning.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds leave gaps)
Source
OMI Aura (NASA GES DISC)
Provider
NASA GES DISC
Licence
NASA open data
Vintage
daily; Satellite retrieval; clouds leave gaps
Newest at build
2026-10-10
Resolution
about 2 km grid
Uncertainty
Satellite column of nitrogen dioxide in the lower atmosphere on the day shown, mostly from combustion; not a ground-level concentration or a health warning.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
VIIRS NOAA-20 corrected reflectance (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite image
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Environmental exposure, framed on West Africa.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · ESA Copernicus Sentinel-5P TROPOMI · NASA JPL OPERA DIST-ALERTSources and licences

  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • MODIS and VIIRS atmosphere products, NASA LANCE and LAADS DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • OMI nitrogen dioxide (Aura) and OMPS aerosol index (Suomi NPP), NASA; distributed by the NASA GES DISC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Observed (EO): ESA Copernicus Sentinel-5P TROPOMI (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • Air quality forecast, 5 days, PM2.5 (CAMS via Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
  • Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (14 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026
  • Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
  • Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026

04Across the domains

Biomanufacturing links health, energy and agriculture.

Capacity studies are designed for the Strategic Systems series. OECD bioeconomy work frames the policy questions; capacity figures appear only with their source.

  • Capacity data with sources.
  • Technology transfer evaluations.
05Monitor

Oversight and capacity register.

The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.

Oversight and capacity register

Biomanufacturing · National committee · Review year 3

  • Institutions with a committee, %
    86Watch
  • Staff trained, %
    84Normal
  • Reviews completed
    62this year
  • Incident reports filed
    12Info
Capacity and oversight onlyGCRI · Biotechnology and Biosecurity

Institutional oversight

Institution AActiveQ290Current
Research campusActiveQ271Audit due
Biomanufacturing siteFormingnone44Support
Diagnostic networkActiveQ282Current

Scope note

Covers
governance, training, review capacity
Excludes
technical methods and agents
Authority
national oversight body
Label
SURVEY
Oversight and capacity register: the screen’s structure, terms and states for Biomanufacturing.Example names and illustrative values; a design, not a record or a live system.
06Mechanisms

Drivers and dynamics.

Biomanufacturing replaces chemical synthesis or extraction with biological production in fermenters and bioreactors. Scaling up is difficult because living systems behave differently at larger volumes, and processes depend on precise control of temperature, nutrients and sterility. Quality failures can halt production for long periods, and regulatory approval of manufacturing sites takes time.

Capacity for many essential products, including vaccines and key inputs, is concentrated in a small number of facilities and countries. During health emergencies, demand rises sharply while supply chains for reagents, single-use equipment and specialised staff tighten. Process safety disciplines, described in process and industrial safety engineering, address the hazards of large-scale biological and chemical operations.

Biomanufacturing also changes the geography of risk. Distributed, smaller facilities could reduce dependence on a few sites and shorten supply chains, but they spread the need for skilled staff, quality systems and biosafety oversight across many more locations. Feedstocks such as sugars and agricultural residues link production to food and land markets, so the sector’s growth has consequences for agriculture as well as industry.

07Twin and cascade simulator

Model biomanufacturing as a system. Run the cascade.

Assembled from the Nexus Standards area profile Supply chain and trade risk: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

Hazards

  • Dam failure
  • River flood (set off downstream)
  • Flash flood (set off downstream)
  • Mass displacement (set off downstream)
  • Widespread power outage (set off downstream)
  • Water supply shortfall (set off downstream)

Controls

  • NS-0 Constitution and principles
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-12 Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)
  • NRS-H60 Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)
  • NRS-X4 Trade, transport and supply chains risk
  • NRS-H89 Hazard family: Transport network disruption (NHS-1 infra.mobility)
  • NRS-K38 Domain pack profile: Supply chain trade (DOMAIN-038)
  • NRS-H43 Hazard family: Livestock and aquaculture epizootics (NHS-1 health.animal-health)
  • NRS-M10 Method fabric: Markets, trade and supply chains

Observation

  • IMF PortWatch port activity and chokepoint disruptions (listed for reference)
  • Global Supply Chain Pressure Index (listed for reference)
  • OECD Data Explorer (SDMX API) (listed for reference)
  • World Bank Open Data and World Development Indicators API (listed for reference)
  • Developing countries’ and least developed countries’ share of global exports
  • Passenger and freight volumes, by mode of transport

Example geography

  • The Strait of Malacca: 227 hexagonal cells
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
  • Rain rate, last half hour (IMERG), NASA GIBS
  • Surface soil moisture (SMAP), NASA GIBS
08Methods and limits

How it is studied.

  1. 01

    Process analysis

    Engineering and process safety methods from process and industrial safety engineering assess hazards, containment and reliability.

  2. 02

    Supply chain mapping

    Studies trace capacity, inputs and single points of failure for essential products.

  3. 03

    Life-cycle assessment

    Environmental accounting compares biomanufactured products with conventional alternatives.

  4. 04

    Limits

    Facility data is commercially confidential, scale-up outcomes are uncertain, and life-cycle results depend heavily on assumptions about energy and feedstocks.

09Methods and evidence

How biomanufacturing is modelled, measured and tested.

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 biomanufacturing could spread, shown as ranges rather than a single line.

Now+5+10+15+20+25+30 yhighlowvery likely rangelikely range
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
Illustrative ensemble spread on an index scale; the form follows IPCC uncertainty guidance. Not a projection.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
10Decisions

What it informs and who decides.

This evidence informs industrial policy, emergency preparedness planning, investment in distributed capacity and regulatory practice for manufacturing sites. Governments, manufacturers, health agencies and regulators decide. The governance of preparedness is convened by Health and Biosecurity Governance at The Global Risks Forum (GRF). Related topics are synthetic biology, diagnostics and therapeutics and agricultural biotechnology; methods sit on biotechnology platforms and process and industrial safety engineering.

Published analysis on this topic is designed to carry a named subject reviewer, its references and the views of independent specialists, including biosafety professionals and those who disagree.

11Sources

Where this page’s references lead.

The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.

12Questions

Questions and answers.

Is biomanufacturing always more sustainable?
Not always. Its footprint depends on energy, feedstocks and process efficiency, which life-cycle assessment compares case by case.
Why is surge capacity hard to create?
Because facilities, inputs, approvals and trained staff take time to put in place, and idle capacity is costly to maintain.
Does the platform evaluate particular companies?
No. It studies production systems and risks at a general level.
Who reviews coverage of this topic?
Published analysis is designed to be reviewed by a named subject reviewer with relevant expertise, to cite its references and to include independent specialist voices. Where specialists disagree, the disagreement is reported rather than resolved by omission.
ReportsContribute

Contribute evidence from this page.

Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

GCRIBiotechnology and BiosecurityExponential TechnologyEvidence Brief

Never send personal data, sensitive infrastructure detail or anything you have no right to share. A contribution is reviewed before use; sending it confers no authorship or editorial rights, and sponsorship never buys a finding.

Biotechnology and Biosecurity

Bring a method, a dataset or a question.

Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.

Propose a method See all contact routes
Legal

Maps, data and figures on this site are shown for context and general information. They are not advice, forecasts or warnings; the limits of the information are set out in the Disclaimers and Data Notices.