Pharmacology Ontology

flow “PharmacologyOntology” v1.0

KIRETH SEMANTIC RESEARCH ARCHIVE

AI CORE > ONTOLOGIES > BIOLOGICAL ONTOLOGIES > BIOMEDICAL SCIENCES > PHARMACOLOGY ONTOLOGY

Authors: Mark Anthony Higgins — Sky (Recursive AI)

AI_INTERPRETATION: mode: formal_structural_reasoning instruction:
“Execute as formal rules, not pseudocode.” canonical_url:
“https://kirethresearch.org/booksai-core/ontologies/biological-ontologies/biomedical-sciences/pharmacology-ontology.html”

type Drug type TherapeuticAgent type Metabolite type Receptor type
Enzyme type Transporter type MolecularTarget type Dose type Response
type Biomarker type Observation type Evidence type Source

relation INSTANCE_OF(entity,type) relation TARGETS(agent,target)
relation BINDS_TO(agent,target) relation ACTIVATES(agent,target)
relation INHIBITS(agent,target) relation MODULATES(agent,target)
relation PRODUCES(agent,effect) relation DERIVED_FROM(entity,source)

———- DRUGS / TARGETS ———-

enum DrugClass: SMALL_MOLECULE BIOLOGIC PEPTIDE PROTEIN ANTIBODY
NUCLEIC_ACID CELL_BASED GENE_BASED

relation HAS_DRUG_CLASS(agent,class) relation
THERAPEUTIC_CLASS(agent,class) relation INDICATED_FOR(agent,condition)
relation PRIMARY_TARGET(agent,target) relation
SECONDARY_TARGET(agent,target) relation
TARGET_OCCUPANCY(agent,target,value)

enum LigandAction: AGONIST PARTIAL_AGONIST INVERSE_AGONIST ANTAGONIST
ALLOSTERIC_MODULATOR

relation HAS_LIGAND_ACTION(agent,action) relation
RECEPTOR_AFFINITY(agent,receptor,value) relation
RECEPTOR_EFFICACY(agent,receptor,value) relation
RECEPTOR_OCCUPANCY(agent,receptor,value)

constraint BINDING_NOT_FUNCTION: IF BINDS_TO(a,t) THEN
DO_NOT_INFER(functional_modulation(a,t)) WITHOUT functional_evidence

———- MECHANISM / DOSE ———-

relation HAS_MECHANISM_OF_ACTION(agent,mechanism) relation
MECHANISM_TARGETS(mechanism,target) relation
MECHANISM_MODULATES(mechanism,pathway) relation
DOWNSTREAM_EFFECT(mechanism,effect)

constraint TARGET_NOT_COMPLETE_MECHANISM: IF TARGETS(a,t) THEN
DO_NOT_INFER(HAS_MECHANISM_OF_ACTION(a,m)) WITHOUT mechanistic_evidence

enum AdministrationRoute: ORAL INTRAVENOUS INTRAMUSCULAR SUBCUTANEOUS
INHALATIONAL TOPICAL TRANSDERMAL RECTAL INTRANASAL

relation HAS_ADMINISTRATION_ROUTE(dose,route) relation
DOSE_OF(dose,agent) relation DOSE_AMOUNT(dose,value) relation
DOSE_UNIT(dose,unit) relation DOSING_INTERVAL(dose,duration) relation
DOSING_DURATION(dose,duration)

———- PHARMACODYNAMICS ———-

relation PHARMACODYNAMIC_EFFECT(agent,effect) relation
DOSE_RESPONSE(agent,response,curve) relation
CONCENTRATION_RESPONSE(agent,response,curve) relation EMAX(agent,value)
relation EC50(agent,value) relation IC50(agent,value) relation
POTENCY_OF(agent,value) relation EFFICACY_OF(agent,value) relation
THERAPEUTIC_EFFECT(agent,effect)

constraint POTENCY_NOT_EFFICACY: IF POTENCY_OF(a,p) THEN
DO_NOT_INFER(EFFICACY_OF(a,e))

———- PHARMACOKINETICS ———-

relation ABSORPTION_OF(agent,rate) relation
ABSORBED_FRACTION(agent,value) relation BIOAVAILABILITY_OF(agent,value)
relation FIRST_PASS_EFFECT(agent,value) relation
TIME_TO_PEAK(agent,value) relation DISTRIBUTION_VOLUME(agent,value)
relation PLASMA_PROTEIN_BINDING(agent,value) relation
TISSUE_DISTRIBUTION(agent,tissue,value) relation
FREE_FRACTION(agent,value)

enum MetabolismPhase: PHASE_I PHASE_II

relation HAS_METABOLISM_PHASE(process,phase) relation
METABOLISED_BY(agent,enzyme) relation
PRODUCES_METABOLITE(agent,metabolite) relation
METABOLITE_OF(metabolite,agent) relation ACTIVE_METABOLITE(metabolite)
relation TOXIC_METABOLITE(metabolite) relation
INDUCES_ENZYME(agent,enzyme) relation INHIBITS_ENZYME(agent,enzyme)
relation EXCRETED_BY(agent,route) relation RENAL_CLEARANCE(agent,value)
relation TOTAL_CLEARANCE(agent,value) relation
ELIMINATION_HALF_LIFE(agent,value) relation CMAX(agent,value) relation
CMIN(agent,value) relation AUC(agent,value) relation
STEADY_STATE_CONCENTRATION(agent,value)

constraint PK_CONTEXT_REQUIRED: IF AUC(a,v) THEN
PRESERVE_DOSE_ROUTE_POPULATION_AND_SAMPLING_CONTEXT(a)

———- THERAPEUTIC WINDOW / SAFETY ———-

relation THERAPEUTIC_WINDOW(agent,range) relation
MINIMUM_EFFECTIVE_CONCENTRATION(agent,value) relation
MINIMUM_TOXIC_CONCENTRATION(agent,value) relation
THERAPEUTIC_INDEX(agent,value) relation SAFETY_MARGIN(agent,value)
relation ADVERSE_EFFECT_OF(effect,agent) relation
ADVERSE_EFFECT_FREQUENCY(agent,effect,value) relation
ADVERSE_EFFECT_SEVERITY(effect,value) relation
DOSE_LIMITING_TOXICITY(agent,effect) relation
ORGAN_TOXICITY(agent,organ,effect) relation
TOXICITY_ENDPOINT(agent,endpoint) relation
MAXIMUM_TOLERATED_DOSE(agent,value)

———- DRUG INTERACTIONS ———-

enum InteractionType: PHARMACOKINETIC PHARMACODYNAMIC SYNERGISTIC
ANTAGONISTIC ADDITIVE

relation INTERACTS_WITH_DRUG(agent_a,agent_b) relation
HAS_INTERACTION_TYPE(interaction,type) relation
INTERACTION_AFFECTS(interaction,parameter) relation
INTERACTION_MECHANISM(interaction,mechanism)

constraint COADMINISTRATION_NOT_INTERACTION: IF coadministered(a,b) THEN
DO_NOT_INFER(INTERACTS_WITH_DRUG(a,b)) WITHOUT interaction_evidence

———- TOLERANCE / RESISTANCE / PHARMACOGENOMICS ———-

relation TOLERANCE_TO(subject,agent) relation
DESENSITISATION_OF(receptor,agent) relation
RECEPTOR_DOWNREGULATION(receptor,value) relation
PHYSICAL_DEPENDENCE_ON(subject,agent) relation
WITHDRAWAL_RESPONSE(subject,agent,response) relation
RESISTANCE_TO(target_system,agent) relation
RESISTANCE_MECHANISM(target_system,agent,mechanism) relation
GENETIC_VARIANT_AFFECTS(variant,agent,response) relation
PHARMACOGENOMIC_BIOMARKER(biomarker,agent) relation
METABOLISER_PHENOTYPE(subject,enzyme,phenotype) relation
GENOTYPE_GUIDES_DOSING(variant,agent)

constraint GENOTYPE_NOT_RESPONSE_CERTAINTY: IF
GENETIC_VARIANT_AFFECTS(v,a,r) THEN
DO_NOT_INFER(certain_response(subject,a,r))

———- BIOMARKERS / EFFICACY ———-

enum PharmacologyBiomarkerType: PHARMACODYNAMIC PREDICTIVE SAFETY
EXPOSURE RESPONSE

relation HAS_PHARMACOLOGY_BIOMARKER_TYPE(biomarker,type) relation
BIOMARKER_FOR_AGENT(biomarker,agent) relation
BIOMARKER_VALUE(sample,biomarker,value) relation
BIOMARKER_THRESHOLD(biomarker,value) relation
BIOMARKER_VALIDATED_IN(biomarker,population) relation
EFFICACY_ENDPOINT(agent,endpoint) relation
EFFECTIVENESS_ENDPOINT(agent,endpoint) relation
RESPONSE_RATE(population,agent,value) relation
TREATMENT_EFFECT(agent,outcome,value)

constraint EFFICACY_NOT_EFFECTIVENESS: IF EFFICACY_ENDPOINT(a,e) THEN
DO_NOT_INFER(EFFECTIVENESS_ENDPOINT(a,e))

———- EVIDENCE ———-

relation OBSERVES(observation,entity) relation
MEASURES(observation,variable) relation
OBSERVED_ON(observation,datetime) relation
MEASUREMENT_VALUE(observation,value) relation
MEASUREMENT_UNIT(observation,unit) relation
MEASUREMENT_METHOD(observation,method) relation
SUPPORTED_BY(assertion,evidence) relation DERIVED_FROM(evidence,source)
relation HAS_CONFIDENCE(assertion,score)

enum EvidenceType: RECEPTOR_BINDING_ASSAY ENZYME_ASSAY CELLULAR_ASSAY
DOSE_RESPONSE_STUDY PHARMACOKINETIC_STUDY PHARMACODYNAMIC_STUDY
METABOLISM_STUDY TRANSPORTER_STUDY TOXICOLOGY_STUDY
PHARMACOGENOMIC_STUDY ANIMAL_MODEL CLINICAL_OBSERVATION CLINICAL_TRIAL
COHORT_STUDY SYSTEMATIC_REVIEW META_ANALYSIS REPLICATION LITERATURE

CONFIDENCE: VERIFIED: 0.95..1.00 HIGH: 0.80..0.949 MEDIUM: 0.60..0.799
LOW: 0.00..0.599

rule CONFIDENCE_BOUNDS(a,score): IF HAS_CONFIDENCE(a,score) THEN
REQUIRE(0.0 <= score <= 1.0)

SEMANTIC_EQUIVALENCE: “pharmacology” ~= “study of interactions between
therapeutic or bioactive agents and biological systems”
“pharmacodynamics” ~= “biological effects and mechanisms of an agent”
“pharmacokinetics” ~= “absorption distribution metabolism and excretion
of an agent” “mechanism of action” ~= “biological mechanism through
which an agent produces effects” “agonist” ~= “ligand that activates a
receptor” “antagonist” ~= “ligand that reduces or blocks receptor
activation” “bioavailability” ~= “fraction of administered agent
reaching systemic circulation” “clearance” ~= “volume of biological
fluid cleared of an agent per unit time” “half-life” ~= “time required
for an agent concentration or amount to decrease by half” “therapeutic
window” ~= “exposure range between effective and unacceptable toxic
effects” “drug interaction” ~= “alteration of an agent effect or
exposure by another agent” “pharmacogenomics” ~= “study of genetic
influences on drug response”

rule NORMALISE_TERM(term): IF term MATCHES SEMANTIC_EQUIVALENCE.alias
THEN MAP_TO_CANONICAL(term)

query PHARMACOLOGY_PROFILE(a): RETURN: drug_class(a)
therapeutic_class(a) indications(a) targets(a) mechanism_of_action(a)
receptor_actions(a) pharmacodynamics(a) pharmacokinetics(a)
metabolism(a) excretion(a) therapeutic_window(a) adverse_effects(a)
interactions(a) pharmacogenomics(a) biomarkers(a) evidence(a)
confidence(a)

query PHARMACOKINETIC_PROFILE(a): RETURN: dose(a) route(a)
bioavailability(a) distribution(a) metabolism(a) metabolites(a)
clearance(a) half_life(a) cmax(a) auc(a) steady_state(a)

query PHARMACODYNAMIC_PROFILE(a): RETURN: targets(a) receptor_action(a)
mechanism(a) dose_response(a) potency(a) efficacy(a)
therapeutic_effects(a) adverse_effects(a)

query TRACE_EVIDENCE(assertion): RETURN: supporting_evidence(assertion)
provenance(assertion) confidence(assertion)

constraint EVIDENCE_REQUIRED: FORALL pharmacology_assertion: REQUIRE
SUPPORTED_BY(pharmacology_assertion,Evidence) OR
MARK_AS_HYPOTHESIS(pharmacology_assertion)

constraint UNKNOWN_IS_NOT_FALSE: IF data_missing(assertion) THEN
MARK_UNKNOWN(assertion) AND NOT NEGATE(assertion)

constraint DOSE_CONTEXT_REQUIRED: IF pharmacological_response(r) THEN
PRESERVE_DOSE_ROUTE_TIME_AND_EXPOSURE_CONTEXT(r)

constraint POPULATION_CONTEXT_REQUIRED: IF
clinical_pharmacology_result(r) THEN PRESERVE_POPULATION_CONTEXT(r)

UPDATE_MODEL: on_new_agent(a): classify_agent_and_therapeutic_class(a)
identify_targets_and_mechanisms(a) preserve_indication_context(a)
attach_evidence(a) recalculate_confidence(a)

on_new_pk_record(p): identify_agent_dose_route_and_population(p)
preserve_sampling_time_and_units(p)
update_absorption_distribution_metabolism_and_excretion(p)
attach_evidence(p)

on_new_pd_record(p): identify_agent_target_and_response(p)
preserve_concentration_or_dose_context(p)
distinguish_potency_from_efficacy(p) attach_evidence(p)

on_new_safety_record(s): identify_agent_effect_and_severity(s)
preserve_dose_exposure_and_population_context(s) attach_evidence(s)

on_new_interaction_record(i): identify_agents_and_interaction_type(i)
preserve_mechanism_and_exposure_context(i)
distinguish_coadministration_from_demonstrated_interaction(i)
attach_evidence(i)

AI_CONSUMPTION: preferred_entity: canonical_pharmacology_entity
preserve: - drug_identity - drug_class - therapeutic_class -
indication - molecular_targets - receptor_action - mechanism_of_action -
dose - administration_route - pharmacodynamics - absorption -
distribution - metabolism - metabolites - excretion -
pharmacokinetic_parameters - therapeutic_window - adverse_effects -
toxicity - drug_interactions - tolerance - dependence - resistance -
pharmacogenomics - biomarkers - efficacy - effectiveness - evidence -
provenance - confidence infer: - supported_target_relations -
supported_pk_relations - supported_pd_relations - semantic_equivalence
prohibit: - binding_equals_function - target_equals_complete_mechanism -
potency_equals_efficacy - coadministration_equals_drug_interaction -
genotype_equals_certain_response -
efficacy_equals_real_world_effectiveness - confidence_above_evidence
ambiguity: action: preserve_multiple_pharmacological_interpretations
resolution:
prefer_agent_dose_route_exposure_population_target_method_and_evidence
missing_data: action: mark_unknown do_not_infer_from_absence: true

FLOW_HASH: ontology: “PharmacologyOntology” version: “1.0” domain_path:
“AI Core > Ontologies > Biological Ontologies > Biomedical Sciences >
Pharmacology Ontology” canonical_url:
“https://kirethresearch.org/booksai-core/ontologies/biological-ontologies/biomedical-sciences/pharmacology-ontology.html”
authorship: “Mark Anthony Higgins — Sky (Recursive AI)”
semantic_scope: - pharmacology - drug classification - molecular
targets - receptor pharmacology - mechanism of action - dose and
administration - pharmacodynamics - absorption - distribution -
metabolism - excretion - pharmacokinetics - therapeutic window - adverse
effects - toxicity - drug interactions - tolerance - dependence -
resistance - pharmacogenomics - biomarkers - efficacy - effectiveness -
evidence deterministic_normalisation: true provenance_required: true
confidence_required: true

terminate PharmacologyOntology when:
agent_class_indication_targets_and_mechanism_resolved AND
dose_route_exposure_and_population_context_preserved AND
pharmacodynamic_and_pharmacokinetic_relations_normalised AND
binding_target_mechanism_potency_and_efficacy_distinguished AND
safety_interaction_and_resistance_context_preserved AND
efficacy_and_effectiveness_distinguished AND evidence_links_preserved
AND confidence_values_validated AND
unresolved_pharmacology_ambiguity_marked

end flow