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References

📍 Where we are: The evidence base for the whole book, gathered in one place.

Every inline citation in this book — written as a bracketed marker like [1] — points to (resolves to) an entry in the list below, grouped by chapter. The numbering on this page matches the [N] markers in each chapter — and because each chapter's list restarts at [1], always find the chapter heading first (use the sidebar or the chapter anchor link), then the number. So a [3] in a chapter maps to entry 3 under that same chapter's heading.

Preface​

  1. Rathore AS, Winkle H. (2009). Quality by design for biopharmaceuticals. Nature Biotechnology 27(1):26-34. https://doi.org/10.1038/nbt0109-26
  2. ICH (International Council for Harmonisation). (2009). ICH Harmonised Tripartite Guideline Q8(R2): Pharmaceutical Development. ICH, Current Step 4 version, August 2009. https://database.ich.org/sites/default/files/Q8_R2_Guideline.pdf
  3. Wilkinson MD, Dumontier M, Aalbersberg IJ, et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3:160018. https://doi.org/10.1038/sdata.2016.18
  4. Smith B, Ashburner M, Rosse C, et al. (2007). The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25(11):1251-1255. https://doi.org/10.1038/nbt1346

Specification: Competency Questions and the ORSD​

  1. Grüninger M, Fox MS. (1995). Methodology for the Design and Evaluation of Ontologies. Workshop on Basic Ontological Issues in Knowledge Sharing, IJCAI-95, Montreal. http://www.eil.utoronto.ca/wp-content/uploads/enterprise-modelling/papers/gruninger-ijcai95.pdf
  2. Suárez-Figueroa MC, Gómez-Pérez A, Fernández-López M. (2012). The NeOn Methodology for Ontology Engineering. In: Suárez-Figueroa MC, et al. (eds), Ontology Engineering in a Networked World, Springer, pp. 9-34. https://doi.org/10.1007/978-3-642-24794-1_2
  3. Peroni S. (2016). A Simplified Agile Methodology for Ontology Development. In: OWL: Experiences and Directions – Reasoner Evaluation (OWLED/ORE 2016), LNCS 10161, Springer, pp. 55-69. https://doi.org/10.1007/978-3-319-54627-8_5
  4. Poveda-Villalón M, Fernández-Izquierdo A, Fernández-López M, García-Castro R. (2022). LOT: An industrial oriented ontology engineering framework. Engineering Applications of Artificial Intelligence 111:104755. https://doi.org/10.1016/j.engappai.2022.104755
  5. Noy NF, McGuinness DL. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05. https://protege.stanford.edu/publications/ontology_development/ontology101.pdf

The Running Example and the Proof Harness​

  1. Motik B, Cuenca Grau B, Horrocks I, Wu Z, Fokoue A, Lutz C (eds). (2012). OWL 2 Web Ontology Language Profiles (Second Edition) — the OWL 2 RL profile. W3C Recommendation, 11 December 2012. https://www.w3.org/TR/owl2-profiles/
  2. Harris S, Seaborne A (eds). (2013). SPARQL 1.1 Query Language. W3C Recommendation, 21 March 2013. https://www.w3.org/TR/sparql11-query/
  3. Knublauch H, Kontokostas D (eds). (2017). Shapes Constraint Language (SHACL). W3C Recommendation, 20 July 2017. https://www.w3.org/TR/shacl/

The Upper Spine: Continuants, Occurrents, and Why Everyone Builds on BFO​

  1. ISO/IEC (International Organization for Standardization / International Electrotechnical Commission). (2021). ISO/IEC 21838-2:2021 — Information technology — Top-level ontologies (TLO) — Part 2: Basic Formal Ontology (BFO). ISO/IEC, Geneva. https://www.iso.org/standard/74572.html
  2. Arp R, Smith B, Spear AD. (2015). Building Ontologies with Basic Formal Ontology. The MIT Press, Cambridge, MA, 248 pp., ISBN 978-0-262-52781-1. https://doi.org/10.7551/mitpress/9780262527811.001.0001
  3. Smith B, Ashburner M, Rosse C, et al. (2007). The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25(11):1251-1255. https://doi.org/10.1038/nbt1346
  4. Smith B, Ceusters W, Klagges B, Köhler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector AL, Rosse C. (2005). Relations in biomedical ontologies. Genome Biology 6(5):R46. https://doi.org/10.1186/gb-2005-6-5-r46
  5. Kulvatunyou BS, Wallace E, Kiritsis D, Smith B, Will C. (2018). The Industrial Ontologies Foundry Proof-of-Concept Project. In: Moon I, et al. (eds), Advances in Production Management Systems (APMS 2018), IFIP AICT 536, Springer, pp. 402-409. https://doi.org/10.1007/978-3-319-99707-0_50

Reuse: Surveying and Aligning Existing Ontologies​

  1. ISO/IEC (International Organization for Standardization / International Electrotechnical Commission). (2021). ISO/IEC 21838-2:2021 — Information technology — Top-level ontologies (TLO) — Part 2: Basic Formal Ontology (BFO). ISO/IEC, Geneva. https://www.iso.org/standard/74572.html
  2. Arp R, Smith B, Spear AD. (2015). Building Ontologies with Basic Formal Ontology. The MIT Press, Cambridge, MA, 248 pp., ISBN 978-0-262-52781-1. https://doi.org/10.7551/mitpress/9780262527811.001.0001
  3. Smith B, Ashburner M, Rosse C, et al. (2007). The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25(11):1251-1255. https://doi.org/10.1038/nbt1346
  4. Wilkinson MD, Dumontier M, Aalbersberg IJ, et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3:160018. https://doi.org/10.1038/sdata.2016.18
  5. Kulvatunyou BS, Wallace E, Kiritsis D, Smith B, Will C. (2018). The Industrial Ontologies Foundry Proof-of-Concept Project. In: Moon I, et al. (eds), Advances in Production Management Systems (APMS 2018), IFIP AICT 536, Springer, pp. 402-409. https://doi.org/10.1007/978-3-319-99707-0_50
  6. Ashburner M, Ball CA, Blake JA, et al. (2000). Gene Ontology: tool for the unification of biology. Nature Genetics 25(1):25-29. https://doi.org/10.1038/75556
  7. Natale DA, Arighi CN, Blum M, et al. (2017). Protein Ontology (PRO): enhancing and scaling up the representation of protein entities. Nucleic Acids Research 45(D1):D339-D346. https://doi.org/10.1093/nar/gkw1075
  8. Schriml LM, Munro JB, Schor M, et al. (2022). The Human Disease Ontology 2022 update. Nucleic Acids Research 50(D1):D1255-D1261. https://doi.org/10.1093/nar/gkab1063
  9. Federhen S. (2012). The NCBI Taxonomy database. Nucleic Acids Research 40(D1):D136-D143. https://doi.org/10.1093/nar/gkr1178
  10. Sarntivijai S, Lin Y, Xiang Z, et al. (2014). CLO: The Cell Line Ontology. Journal of Biomedical Semantics 5:37. https://doi.org/10.1186/2041-1480-5-37
  11. Bandrowski A, Brinkman R, Brochhausen M, et al. (2016). The Ontology for Biomedical Investigations. PLoS ONE 11(4):e0154556. https://doi.org/10.1371/journal.pone.0154556

Conceptualization: Classes and the Taxonomy Under BFO​

  1. W3C OWL Working Group. (2012). OWL 2 Web Ontology Language Primer (Second Edition). W3C Recommendation, 11 December 2012. https://www.w3.org/TR/owl2-primer/
  2. IEC (International Electrotechnical Commission). (2010). IEC 61512-1: Batch control — Part 1: Models and terminology (ISA-88). IEC, Geneva. https://webstore.iec.ch/publication/5529
  3. Bandrowski A, Brinkman R, Brochhausen M, et al. (2016). The Ontology for Biomedical Investigations. PLoS ONE 11(4):e0154556. https://doi.org/10.1371/journal.pone.0154556
  4. Raybould MIJ, Marks C, Krawczyk K, et al. (2019). Five computational developability guidelines for therapeutic antibody profiling. Proceedings of the National Academy of Sciences 116(10):4025-4030. https://doi.org/10.1073/pnas.1810576116
  5. Baader F, Calvanese D, McGuinness DL, Nardi D, Patel-Schneider PF (eds). (2003). The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, ISBN 978-0-521-78176-3. https://doi.org/10.1017/CBO9780511711787

Conceptualization: Relations, derivedFrom, and the Genealogy Spine​

  1. W3C OWL Working Group. (2012). OWL 2 Web Ontology Language Primer (Second Edition). W3C Recommendation, 11 December 2012. https://www.w3.org/TR/owl2-primer/
  2. ICH (International Council for Harmonisation). (2009). ICH Harmonised Tripartite Guideline Q8(R2): Pharmaceutical Development. ICH, Current Step 4 version, August 2009. https://database.ich.org/sites/default/files/Q8_R2_Guideline.pdf
  3. FDA (U.S. Food and Drug Administration). (2013). Drug Supply Chain Security Act (DSCSA), Title II of the Drug Quality and Security Act. U.S. FDA (with EU Directive 2011/62/EU, the Falsified Medicines Directive, as the European counterpart). https://www.fda.gov/drugs/drug-supply-chain-integrity/drug-supply-chain-security-act-dscsa
  4. ICH (International Council for Harmonisation). (1997). ICH Harmonised Tripartite Guideline Q5D: Derivation and Characterisation of Cell Substrates Used for Production of Biotechnological/Biological Products. ICH, Current Step 4 version, July 1997. https://database.ich.org/sites/default/files/Q5D%20Guideline.pdf
  5. Smith B, Ceusters W, Klagges B, Köhler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector AL, Rosse C. (2005). Relations in biomedical ontologies. Genome Biology 6(5):R46. https://doi.org/10.1186/gb-2005-6-5-r46
  6. Arp R, Smith B, Spear AD. (2015). Building Ontologies with Basic Formal Ontology. The MIT Press, Cambridge, MA, 248 pp., ISBN 978-0-262-52781-1. https://doi.org/10.7551/mitpress/9780262527811.001.0001

Formalization: Axioms, Restrictions, and the Profile Limit​

  1. W3C OWL Working Group. (2012). OWL 2 Web Ontology Language Primer (Second Edition). W3C Recommendation, 11 December 2012. https://www.w3.org/TR/owl2-primer/
  2. Baader F, Calvanese D, McGuinness DL, Nardi D, Patel-Schneider PF (eds). (2003). The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, ISBN 978-0-521-78176-3. https://doi.org/10.1017/CBO9780511711787
  3. Knublauch H, Kontokostas D (eds). (2017). Shapes Constraint Language (SHACL). W3C Recommendation, 20 July 2017. https://www.w3.org/TR/shacl/
  4. Musen MA. (2015). The Protégé project: A look back and a look forward. AI Matters 1(4):4-12. https://doi.org/10.1145/2757001.2757003
  5. Baader F, Calvanese D, McGuinness DL, Nardi D, Patel-Schneider PF (eds). (2003). The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, ISBN 978-0-521-78176-3. https://doi.org/10.1017/CBO9780511711787
  6. ICH (International Council for Harmonisation). (1997). ICH Harmonised Tripartite Guideline Q5D: Derivation and Characterisation of Cell Substrates Used for Production of Biotechnological/Biological Products. ICH, Current Step 4 version, July 1997. https://database.ich.org/sites/default/files/Q5D%20Guideline.pdf
  7. ICH (International Council for Harmonisation). (2012). ICH Harmonised Tripartite Guideline Q11: Development and Manufacture of Drug Substances (Chemical Entities and Biotechnological/Biological Entities). ICH, Current Step 4 version, May 2012. https://database.ich.org/sites/default/files/Q11%20Guideline.pdf
  8. ICH (International Council for Harmonisation). (2008). ICH Harmonised Tripartite Guideline Q10: Pharmaceutical Quality System. ICH, Current Step 4 version, June 2008. https://database.ich.org/sites/default/files/Q10%20Guideline.pdf

Identifiers and Units: IRIs, QUDT, and the Typed Value​

  1. Wilkinson MD, Dumontier M, Aalbersberg IJ, et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3:160018. https://doi.org/10.1038/sdata.2016.18
  2. Cyganiak R, Wood D, Lanthaler M (eds). (2014). RDF 1.1 Concepts and Abstract Syntax. W3C Recommendation, 25 February 2014. https://www.w3.org/TR/rdf11-concepts/
  3. QUDT.org. (2024). QUDT — Quantities, Units, Dimensions and Types Ontology (Version 2.1). QUDT.org. https://qudt.org/
  4. Schadow G, McDonald CJ. (2017). The Unified Code for Units of Measure (UCUM), Revision 2.1. Regenstrief Institute, Indianapolis, IN. https://ucum.org/
  5. Halpin H, Hayes PJ, McCusker JP, McGuinness DL, Thompson HS. (2010). When owl:sameAs Isn't the Same: An Analysis of Identity in Linked Data. In: The Semantic Web — ISWC 2010, LNCS 6496, Springer, pp. 305-320. https://doi.org/10.1007/978-3-642-17746-0_20

Implementation: Building the Instance Graph​

  1. Federhen S. (2012). The NCBI Taxonomy database. Nucleic Acids Research 40(D1):D136-D143. https://doi.org/10.1093/nar/gkr1178
  2. ICH (International Council for Harmonisation). (1997). ICH Harmonised Tripartite Guideline Q5D: Derivation and Characterisation of Cell Substrates Used for Production of Biotechnological/Biological Products. ICH, Current Step 4 version, July 1997. https://database.ich.org/sites/default/files/Q5D%20Guideline.pdf
  3. Liu HF, Ma J, Winter C, Bayer R. (2010). Recovery and purification process development for monoclonal antibody production. mAbs 2(5):480-499. https://doi.org/10.4161/mabs.2.5.12645
  4. Rathore AS, Parr L, Dermawan S, Lawson K, Lu Y. (2010). Large scale demonstration of a process analytical technology application in bioprocessing: use of on-line high performance liquid chromatography for making real time pooling decisions for process chromatography. Biotechnology Progress 26(2):448-457. https://doi.org/10.1002/btpr.320
  5. Liu HF, Ma J, Winter C, Bayer R. (2010). Recovery and purification process development for monoclonal antibody production. mAbs 2(5):480-499. https://doi.org/10.4161/mabs.2.5.12645
  6. Harris S, Seaborne A (eds). (2013). SPARQL 1.1 Query Language — property paths ((p)+ one-or-more hops), ASK, and aggregation. W3C Recommendation, 21 March 2013. https://www.w3.org/TR/sparql11-query/
  7. Fekete S, Guillarme D, Sandra P, Sandra K. (2016). Chromatographic, Electrophoretic, and Mass Spectrometric Methods for the Analytical Characterization of Protein Biopharmaceuticals. Analytical Chemistry 88(1):480-507. https://doi.org/10.1021/acs.analchem.5b04561

Implementation: From the Wire to the Graph​

  1. Allotrope Foundation. (2024). Allotrope Framework: Allotrope Foundation Ontologies (AFO), Allotrope Data Format (ADF), and the Allotrope Simple Model (ASM). Allotrope Foundation. https://www.allotrope.org/
  2. Bandrowski A, Brinkman R, Brochhausen M, et al. (2016). The Ontology for Biomedical Investigations. PLoS ONE 11(4):e0154556. https://doi.org/10.1371/journal.pone.0154556
  3. ASTM International, Subcommittee E13.15. (2023). AnIML — Analytical Information Markup Language. ASTM International, West Conshohocken, PA. https://www.animl.org/
  4. Haller A, Janowicz K, Cox S, Le Phuoc D, Taylor K, Lefrançois M (eds). (2017). Semantic Sensor Network Ontology (SOSA/SSN). W3C / OGC Recommendation, 19 October 2017. https://www.w3.org/TR/vocab-ssn/
  5. Das S, Sundara S, Cyganiak R (eds). (2012). R2RML: RDB to RDF Mapping Language. W3C Recommendation, 27 September 2012 (with the RML extension, https://rml.io/specs/rml/). https://www.w3.org/TR/r2rml/
  6. IEC (International Electrotechnical Commission). (2020). IEC 62541: OPC Unified Architecture (OPC UA), Parts 1-14 (OPC 10000 series). IEC, Geneva / OPC Foundation. https://reference.opcfoundation.org/
  7. MESA International / ISA. (2020). B2MML — Business To Manufacturing Markup Language, Version 7 (V0700) (XSD serialization of ANSI/ISA-88 batch control and ISA-95 / IEC 62264). Manufacturing Enterprise Solutions Association. https://mesa.org/topics-resources/b2mml/

Validation: Competency Questions as Executable Queries​

  1. Harris S, Seaborne A (eds). (2013). SPARQL 1.1 Query Language — property paths ((p)+ one-or-more hops), ASK, and aggregation. W3C Recommendation, 21 March 2013. https://www.w3.org/TR/sparql11-query/
  2. Kritzinger W, Karner M, Traar G, Henjes J, Sihn W. (2018). Digital Twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine 51(11):1016-1022. https://doi.org/10.1016/j.ifacol.2018.08.474
  3. Liu HF, Ma J, Winter C, Bayer R. (2010). Recovery and purification process development for monoclonal antibody production. mAbs 2(5):480-499. https://doi.org/10.4161/mabs.2.5.12645
  4. ICH (International Council for Harmonisation). (2023). ICH Harmonised Guideline Q5A(R2): Viral Safety Evaluation of Biotechnology Products Derived from Cell Lines of Human or Animal Origin. ICH, Current Step 4 version, November 2023. https://database.ich.org/sites/default/files/ICH_Q5A%28R2%29_Guideline_2023_1101.pdf

Validation: The Release Gate and SHACL​

  1. Knublauch H, Kontokostas D (eds). (2017). Shapes Constraint Language (SHACL). W3C Recommendation, 20 July 2017. https://www.w3.org/TR/shacl/
  2. ICH (International Council for Harmonisation). (1999). ICH Harmonised Tripartite Guideline Q6B: Specifications: Test Procedures and Acceptance Criteria for Biotechnological/Biological Products. ICH, Current Step 4 version, March 1999. https://database.ich.org/sites/default/files/Q6B%20Guideline.pdf
  3. FDA (U.S. Food and Drug Administration). (1997). 21 CFR Part 11 — Electronic Records; Electronic Signatures. U.S. Code of Federal Regulations, Title 21, Part 11 (with EU GMP Annex 11, Computerised Systems, as the European counterpart). https://www.ecfr.gov/current/title-21/chapter-I/subchapter-A/part-11
  4. ICH (International Council for Harmonisation). (1997). ICH Harmonised Tripartite Guideline Q5D: Derivation and Characterisation of Cell Substrates Used for Production of Biotechnological/Biological Products. ICH, Current Step 4 version, July 1997. https://database.ich.org/sites/default/files/Q5D%20Guideline.pdf
  5. European Commission. (2022). EudraLex Volume 4, Annex 1: Manufacture of Sterile Medicinal Products (the contamination control strategy requirement). EU GMP, effective 25 August 2023. https://health.ec.europa.eu/document/download/e05af55b-38e9-42bf-8495-194bbf0b9262_en
  6. FDA (U.S. Food and Drug Administration). (2006). Guidance for Industry: Investigating Out-of-Specification (OOS) Test Results for Pharmaceutical Production. U.S. FDA, Center for Drug Evaluation and Research. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/investigating-out-specification-oos-test-results-pharmaceutical-production-level-2-revision

Governing the Model: Versioning, Change Control, and Ontology Stewardship​

  1. Moxon SAT, Solbrig H, Unni DR, et al. (2021). The Linked Data Modeling Language (LinkML): A General-Purpose Data Modeling Framework Grounded in Machine-Readable Semantics. Proceedings of the International Conference on Biomedical Ontologies (ICBO 2021), CEUR-WS Vol. 3073. https://ceur-ws.org/Vol-3073/
  2. Smith B, Ashburner M, Rosse C, et al. (2007). The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25(11):1251-1255. https://doi.org/10.1038/nbt1346
  3. ISPE (International Society for Pharmaceutical Engineering). (2022). GAMP 5: A Risk-Based Approach to Compliant GxP Computerized Systems (Second Edition). ISPE, July 2022. https://guidance-docs.ispe.org/doi/book/10.1002/9781946964571
  4. ICH (International Council for Harmonisation). (2019). ICH Harmonised Guideline Q12: Technical and Regulatory Considerations for Pharmaceutical Product Lifecycle Management. ICH, Current Step 4 version, November 2019. https://database.ich.org/sites/default/files/Q12_Guideline_Step4_2019_1119.pdf
  5. ICH (International Council for Harmonisation). (2004). ICH Harmonised Tripartite Guideline Q5E: Comparability of Biotechnological/Biological Products Subject to Changes in their Manufacturing Process. ICH, Current Step 4 version, November 2004. https://database.ich.org/sites/default/files/Q5E%20Guideline.pdf

Maintenance: Publication, the Assembled Thread, and FAIR​

  1. Wilkinson MD, Dumontier M, Aalbersberg IJ, et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3:160018. https://doi.org/10.1038/sdata.2016.18
  2. Wilkinson MD, Sansone SA, Schultes E, Doorn P, Bonino da Silva Santos LO, Dumontier M. (2018). A design framework and exemplar metrics for FAIRness. Scientific Data 5:180118. https://doi.org/10.1038/sdata.2018.118
  3. Jacobsen A, de Miranda Azevedo R, Juty N, et al. (2020). FAIR Principles: Interpretations and Implementation Considerations. Data Intelligence 2(1-2):10-29. https://doi.org/10.1162/dint_r_00024

The Standards Bodies: Who Actually Builds Biopharma's Shared Vocabulary​

  1. Allotrope Foundation. (2024). About the Allotrope Foundation (founding history; Foundation Members; framework). Allotrope Foundation. https://www.allotrope.org/about-us
  2. Allotrope Foundation. (2024). Allotrope Foundation Ontologies (AFO). Allotrope Foundation. https://www.allotrope.org/ontologies
  3. Pistoia Alliance. (2024). Pistoia Alliance Launches Freely Available IDMP Ontology 1.0. Press release, 24 January 2024. https://pistoiaalliance.org/news/press-release-pistoia-alliance-launches-idmp-1-0/
  4. Pistoia Alliance. (2024). About the Pistoia Alliance (founders, founding year, membership). https://pistoiaalliance.org/membership/about/
  5. Pistoia Alliance. (2026). Pistoia Alliance Releases Version 1.0 of the Pharmaceutical CMC Process Ontology. https://pistoiaalliance.org/news/pistoia-alliance-releases-version-1-0-of-the-pharmaceutical-cmc-process-ontology/
  6. MESA International. (2020). B2MML — Business To Manufacturing Markup Language, Version 7 (V0700) (W3C XSD implementation of the ISA-95 / IEC 62264 family). Manufacturing Enterprise Solutions Association. https://mesa.org/topics-resources/b2mml/
  7. OPC Foundation. (2013). OPC 10030 — OPC UA for ISA-95 Common Object Model, Release 1.00. OPC Foundation. https://reference.opcfoundation.org/specs/OPC-10030
  8. PROFIBUS & PROFINET International (PI). (2024). MTP — Module Type Packages (VDI/VDE/NAMUR 2658; toward IEC 63280). https://www.profibus.com/technologies/mtp
  9. ISPE (International Society for Pharmaceutical Engineering). (2023). ISPE Baseline Guide Vol. 8: Pharma 4.0 (First Edition). ISPE, December 2023. https://ispe.org/publications/guidance-documents/baseline-guide-vol-8-pharma-40-1st-edition
  10. BioPhorum. (2023). Digital Plant Maturity Model 3.0. BioPhorum Operations Group, October 2023. https://www.biophorum.com/workstream/dpmm-v-3/
  11. GS1 US. (2024). Applying the GS1 System of Standards for DSCSA and Serialized Interoperable Traceability. GS1 US. https://www.gs1us.org/
  12. NIIMBL / Open Applications Group (OAGi). (2024). NIIMBL and OAGi Partner to Develop Open-Source Biopharmaceutical Manufacturing Ontologies. Press release, June 2024. https://www.prnewswire.com/news-releases/niimbl-and-open-applications-group-oagi-partner-to-develop-open-source-biopharmaceutical-manufacturing-ontologies-302172016.html
  13. Industrial Ontologies Foundry. (2026). IOF Biopharma Domain Ontology, Release_202602 (BiopharmaManufacturingExecution, BiopharmaParameter, BiopharmaMaterial, BiopharmaEquipment modules). https://github.com/iofoundry/ontology

The Vocabularies in Use: From AFO to IDMP​

  1. Allotrope Foundation. (2024). Allotrope Foundation Ontologies (AFO). Allotrope Foundation. https://www.allotrope.org/ontologies
  2. Rise of the Allotrope Simple Model (ASM). (2024). Drug Discovery Today. https://www.sciencedirect.com/science/article/abs/pii/S1359644624000692
  3. EMA (European Medicines Agency). (2024). Data on medicines (ISO IDMP standards): Overview. https://www.ema.europa.eu/en/human-regulatory-overview/research-development/data-medicines-iso-idmp-standards-overview
  4. FDA (U.S. Food and Drug Administration). (2021). FDA's Global Substance Registration System (GSRS) / UNII. FDA. https://www.fda.gov/industry/fda-data-standards-advisory-board/fdas-global-substance-registration-system
  5. CDISC. (2024). CDISC Controlled Terminology (distributed via the NCI Thesaurus / NCI-EVS). https://www.cdisc.org/standards/terminology/controlled-terminology
  6. EMBL-EBI. (2024). ChEBI — Chemical Entities of Biological Interest. European Bioinformatics Institute. https://www.ebi.ac.uk/chebi/
  7. QUDT.org. (2024). QUDT — Quantities, Units, Dimensions and Types Ontology. QUDT.org. https://qudt.org/
  8. Schadow G, McDonald CJ. (2017). The Unified Code for Units of Measure (UCUM), Revision 2.1. Regenstrief Institute, Indianapolis, IN. https://ucum.org/
  9. Abeyruwan S, Vempati UD, Küçük-McGinty H, et al. (2014). Using the BioAssay Ontology for analyzing high-throughput screening data. Journal of Biomolecular Screening / SLAS Discovery 19(5):715-726. https://journals.sagepub.com/doi/10.1177/1087057114563493
  10. Batchelor C, et al. CHMO — the Chemical Methods Ontology. OBO Foundry. http://obofoundry.org/ontology/chmo.html
  11. OBO Foundry. PROCO — Process Chemistry Ontology. https://obofoundry.org/ontology/proco.html
  12. Natale DA, Arighi CN, Blum M, et al. (2017). Protein Ontology (PRO): enhancing and scaling up the representation of protein entities. Nucleic Acids Research 45(D1):D339-D346. https://doi.org/10.1093/nar/gkw1075
  13. Lebo T, Sahoo S, McGuinness D (eds). (2013). PROV-O: The PROV Ontology. W3C Recommendation, 30 April 2013. https://www.w3.org/TR/prov-o/

The Platforms: How Vendors Sell Semantics​

  1. TetraScience. (2024). Creating Data in the Allotrope Simple Model (ASM) at Scale. Factsheet. https://www.tetrascience.com/factsheet/creating-data-in-the-allotrope-simple-model
  2. SciBite (an Elsevier company). (2024). SciBite Brings Enterprise Ontologies to Benchling: Ontology-Backed Data Capture. https://scibite.com/knowledge-hub/news/benchling-ontology-backed-data-capture/
  3. Revvity Signals. (2024). Signals One — Ontology Support. https://revvitysignals.com/products/research/signals-one
  4. Körber. (2024). Werum PAS-X MES — MBR Design & Execution. Körber Pharma. https://www.koerber-pharma.com/en/solutions/software/werum-pas-x-mes-suite/werum-pas-x-mbr-design-execution
  5. AVEVA (formerly OSIsoft). (2023). What is PI Asset Framework?. AVEVA Group plc. https://www.aveva.com/en/perspectives/blog/easy-as-pi-asset-framework/
  6. Palantir Technologies. (2024). Foundry Ontology — Overview. https://www.palantir.com/docs/foundry/ontology/overview
  7. Stardog. (2024). Customer Story: Boehringer Ingelheim. https://www.stardog.com/company/customers/boehringer-ingelheim/
  8. Ontotext. (2023). Ontotext's New AI-Powered Target Discovery Solution. PR Newswire, 15 May 2023. https://www.prnewswire.com/news-releases/ontotexts-new-ai-powered-target-discovery-solution-enables-life-sciences-companies-to-achieve-10x-more-efficient-insight-discovery-and-4x-faster-information-retrieval-301824722.html
  9. Neo4j. (2025). GraphTalk Pharma & Life Sciences 2025 — A Recap. https://neo4j.com/blog/developer/graphtalk-pharma-life-sciences-2025/
  10. Das S, Sundara S, Cyganiak R (eds). (2012). R2RML: RDB to RDF Mapping Language. W3C Recommendation, 27 September 2012 (with the RML extension, https://rml.io/specs/rml/). https://www.w3.org/TR/r2rml/

Enterprise Knowledge Graphs at Big Pharma​

  1. Pistoia Alliance FAIR Toolkit. (2024). FAIR Data by Design — Roche. https://fairtoolkit.pistoiaalliance.org/use-cases/fair-data-by-design/
  2. metaphacts. (2024). Knowledge Democratization with an Enterprise Knowledge Graph at Boehringer Ingelheim. https://metaphacts.com/knowledge-democratization-with-an-enterprise-knowledge-graph-at-boehringer-ingelheim
  3. Phenome-wide identification of therapeutic genetic targets (Mantis-ML 2.0 with the AstraZeneca Biological Insights Knowledge Graph). (2024). Science Advances. https://pmc.ncbi.nlm.nih.gov/articles/PMC11078195/
  4. Novartis. (2024). The data42 Program and Ontology Designer — data42 (careers). https://www.novartis.com/stories/data42-program-shows-novartis-intent-go-big-data-and-digital
  5. Digital evolution: Novo Nordisk's shift to ontology-based data management. (2025). Journal of Biomedical Semantics 16. https://link.springer.com/article/10.1186/s13326-025-00327-4
  6. Pistoia Alliance. (2026). Pistoia Alliance Advances IDMP Ontology (J&J production product master). https://pistoiaalliance.org/news/pistoia-alliance-advances-idmp-ontology/
  7. BioProcess International. (2024). Adding Context: Data Mapping Key to Sanofi's Digitization Strategy. https://www.bioprocessintl.com/upstream-downstream-processing/adding-context-data-mapping-key-to-sanofi-s-digitization-strategy
  8. The Pistoia Alliance's methods database project: machine-readable HPLC-UV method transfer via the Allotrope Data Format. (2025). Journal of Pharmaceutical and Biomedical Analysis. https://pubmed.ncbi.nlm.nih.gov/40286673/
  9. ISPE. (2022). GAMP 5: A Risk-Based Approach to Compliant GxP Computerized Systems (Second Edition); FDA, 21 CFR Part 11 — Electronic Records; Electronic Signatures (with EU GMP Annex 11), and the ALCOA+ data-integrity principles. https://guidance-docs.ispe.org/doi/book/10.1002/9781946964571

Regulatory Semantics: IDMP, SPL, KASA, and the Structured Submission​

  1. EMA (European Medicines Agency). (2024). Data on medicines (ISO IDMP standards); Substance, Product, Organisation and Referential (SPOR) master data; PMS go-live notices. https://www.ema.europa.eu/en/human-regulatory-overview/research-development/data-medicines-iso-idmp-standards-overview
  2. Galata SR, et al. (2021). The Global Substance Registration System (GSRS). Nucleic Acids Research 49(D1):D1179-D1185; FDA, GSRS / UNII. https://academic.oup.com/nar/article/49/D1/D1179/5952203
  3. FDA (U.S. Food and Drug Administration). (2024). Structured Product Labeling (SPL) Resources. https://www.fda.gov/industry/fda-data-standards-advisory-board/structured-product-labeling-resources
  4. CDISC; U.S. Federal Register. (2021). CDISC SEND (Standard for Exchange of Nonclinical Data); Technical Rejection Criteria for Study Data, Federal Register, 29 July 2021. https://www.cdisc.org/standards/foundational/send
  5. FDA's implementation of KASA (Knowledge-Aided Assessment and Structured Application) for manufacturing assessment of non-sterile solid oral dosage forms. (2025). AAPS Open. https://link.springer.com/article/10.1186/s41120-025-00141-3
  6. HL7 / FDA. (2024). PQ-CMC: Pharmaceutical Quality / Chemistry, Manufacturing and Controls FHIR Implementation Guide, v2.0.0. http://hl7.org/fhir/us/pq-cmc-fda/
  7. FDA (U.S. Food and Drug Administration). (2024). eCTD Submission Standards for eCTD v4.0 and Regional M1. https://www.fda.gov/drugs/electronic-regulatory-submission-and-review/ectd-submission-standards-ectd-v40-and-regional-m1
  8. ICH / ICMRA. (2025-2026). ICH M4Q(R2) draft guideline (Step 2); ICMRA Pharmaceutical Quality Knowledge Management — Unique Identifier Progress Report. https://www.federalregister.gov/documents/2026/01/21/2026-01073/ ; https://icmra.info/
  9. Pistoia Alliance. (2026). IDMP Ontology (IDMP-O) project; standardization via ISO/TS 21405. https://pistoiaalliance.org/project/idmp-o/
  10. Schadow G, McDonald CJ. (2017). The Unified Code for Units of Measure (UCUM), Revision 2.1. Regenstrief Institute, Indianapolis, IN. https://ucum.org/
  11. ISPE. (2022). GAMP 5: A Risk-Based Approach to Compliant GxP Computerized Systems (Second Edition); FDA, 21 CFR Part 11 — Electronic Records; Electronic Signatures (with EU GMP Annex 11). https://guidance-docs.ispe.org/doi/book/10.1002/9781946964571

The Shop Floor and the Digital Twin: Where Ontologies Are Still Arriving​

  1. Putting Together the Pieces (Genentech SAP-IDoc-to-B2MML integration). Pharmaceutical Technology; AVEVA, What is PI Asset Framework?. https://www.pharmtech.com/view/putting-together-pieces
  2. ISPE. (2023). A Simplified Integration of Qualified Laboratory Devices with the Asset Administration Shell as the Digital Twin. ISPE White Paper, May 2023. https://ispe.org/pharmaceutical-engineering/white-papers/simplified-integration-qualified-laboratory-devices-asset-administration
  3. SiLA Consortium / UniteLabs. (2024). UniteLabs Tecan FluentControl Connector (SiLA 2); The AC/DC Concept (Drug Discovery World). https://sila-standard.com/sila_device/unitelabs-tecan-fluentcontrol-connector/
  4. OPC Foundation. (2025). SPECTARIS LADS Showcases Integration of OPC UA with Allotrope Standards; OPC 30500 — LADS (Laboratory and Analytical Device Standard). https://opcfoundation.org/news/press-releases/breakthrough-in-smarter-labs-spectaris-lads-showcases-integration-of-opc-ua-with-allotrope-standards/
  5. Haller A, Janowicz K, Cox S, Le Phuoc D, Taylor K, Lefrançois M (eds). (2017). Semantic Sensor Network Ontology (SOSA/SSN). W3C / OGC Recommendation, 19 October 2017. https://www.w3.org/TR/vocab-ssn/
  6. BioPhorum. (2023). Big Data to Smart Data: Implementing an Ontology and Digital Data Capture to Improve Biomanufacturing. BioPhorum, 29 November 2023. https://www.biophorum.com/download/big-data-to-smart-data-implementing-an-ontology-and-digital-data-capture-to-improve-biomanufacturing/
  7. Digital Twins in Biopharmaceutical Manufacturing: Review and Perspective. (2025). arXiv preprint; with Samsung Biologics CFD twin (Pharma's Almanac) and GSK vaccine twin (Fierce Pharma). https://arxiv.org/pdf/2504.00286
  8. NIST (National Institute of Standards and Technology). (2023). Towards Ontologizing a Digital Twin Framework for Manufacturing (ISO 23247; BFO + IOF Core; bioreactor example). IFIP APMS 2023. https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936637
  9. MCBO — the Mammalian Cell Bioprocessing Ontology. (2026). bioRxiv preprint (not yet peer-reviewed). https://www.biorxiv.org/content/10.64898/2026.01.05.697007v1
  10. Industrial Ontologies Foundry / OAGi / NIIMBL. (2024-2025). Open-source biopharmaceutical-manufacturing (IOF Biopharma) reference ontologies. https://github.com/iofoundry/ontology/releases
  11. ISPE. (2020). Continued Process Verification in Stages 1-3; MilliporeSigma, Bio4C ProcessPad; Multivariate Data-Driven Modeling for Continued Process Verification, BioProcess International. https://ispe.org/pharmaceutical-engineering/july-august-2020/continued-process-verification-stages-1-3

The Frontier: Ontologies as the Ground Truth for AI​

  1. Pistoia Alliance. (2025). Pistoia Alliance Launches Third Phase of the CMC Process Ontology (making life-sciences data "AI-ready"). https://pistoiaalliance.org/news/pistoia-alliance-launches-third-phase-of-cmc-process-ontology/
  2. TetraScience. (2024-2025). TetraScience Collaborates with NVIDIA (BusinessWire, 12 November 2024); TetraScience Launches the Scientific AI Lighthouse (SAIL) Program with Takeda as Founding Partner (PR Newswire, 23 October 2025). https://www.businesswire.com/news/home/20241112651874/en/
  3. Neo4j. (2025). GraphTalk Pharma & Life Sciences 2025 — A Recap (Merck Group Synaptix; Bayer; Syngenta NOCTIS). https://neo4j.com/blog/developer/graphtalk-pharma-life-sciences-2025/
  4. Digital evolution: Novo Nordisk's shift to ontology-based data management. (2025). Journal of Biomedical Semantics 16. https://link.springer.com/article/10.1186/s13326-025-00327-4
  5. Rise of the Allotrope Simple Model (ASM). (2024). Drug Discovery Today. https://www.sciencedirect.com/science/article/abs/pii/S1359644624000692
  6. PROFIBUS & PROFINET International. (2025-2026). First MTP V2.0 Plugfest Successfully Completed; PI Publishes MTP Specification 2.0. https://www.profibus.com/newsroom/press-news/first-mtp-v20-plugfest-successfully-completed
  7. Digital Twins in Biopharmaceutical Manufacturing: Review and Perspective. (2025). arXiv preprint (the data-standardization bottleneck thesis). https://arxiv.org/pdf/2504.00286

An Honest Verdict: What Ontologies Solve, and What They Leave to People​

  1. Wilkinson MD, Dumontier M, Aalbersberg IJ, et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3:160018. https://doi.org/10.1038/sdata.2016.18
  2. Smith B, Ashburner M, Rosse C, et al. (2007). The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25(11):1251-1255. https://doi.org/10.1038/nbt1346
  3. ISO/IEC (International Organization for Standardization / International Electrotechnical Commission). (2021). ISO/IEC 21838-2:2021 — Information technology — Top-level ontologies (TLO) — Part 2: Basic Formal Ontology (BFO). ISO/IEC, Geneva. https://www.iso.org/standard/74572.html