Development of Description Framework of Pharmacodynamics Ontology and its Application to Possible Drug-drug Interaction Reasoning
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1 Development of Description Framework of Pharmacodynamics Ontology and its Application to Possible Drug-drug Interaction Reasoning Takeshi IMAI, Ph.D Masayo Hayakawa Kazuhiko OHE, MD, Ph.D The University of Tokyo Hospital, JAPAN
2 Outline 1. Background & Objectives 2. Description framework of pharmacodynamics ontology 3. Application to possible DDI reasoning 4. Experimental results 5. Discussion, limitations and future directions
3 Background Combination of drugs sometimes induces synergistic or antagonistic effects. Some of such drug-drug interactions (DDIs) may cause serious adverse events. DDI information is currently not been well utilized in daily clinical practice. Could have been caused by the lack of consistency in DDI information in the Summaries of Product Characteristics (SPCs) of drugs. (Virty 97) It s necessary to develop a new methodology which leverages machine reasoning and knowledge base to provide DDI information with reasons and certainty regardless of the descriptions in SPCs Ontology is considered to be one effective solutions to describe knowledge formally
4 Objectives 1) To develop a description framework of pharmacodynamics ontology that is necessary for machine reasoning to identify possible DDI pairs based on pharmacodynamic mechanisms. [Out of Scope]: Pharmacokinetic interactions Drugs like antiseptics that directly act against the target. Focusing on signal transduction mechanisms and resultant physiological systems. 2) To develop a methodology to identify different types of possible DDI pairs based on the ontology and to investigate the effectiveness in an example domain.
5 Description framework of pharmacodynamics ontology
6 Fundamental model of Pharmacodynamics DDIs - three-layered model - Medicine Signal Transduction Process (STP) Physiological Chain (PC) target process Single drug molecules promoting or inhibiting physiological Response target sub-process Physiological state Physiological chain Pharmacological effect
7 Fundamental model of Pharmacodynamics DDIs Noradrenaline STP - three-layered model - Propranolol Medicine Signal Transduction Process (STP) Physiological Chain (PC) Single drug molecules inhibiting target sub-process Bind on the cell membrane physiological Response Blood Pressure Decrease Physiological state Propranolol Hydrochloride Physiological chain Pharmacological effect
8 Pharmacodynamic DDIs will then occur on several points!
9 Fundamental model of Pharmacodynamics DDIs - three-layered model - Medicine Signal Transduction Process (STP) Physiological Chain (PC) A target process C Single drug molecules B D F E Synergistic / Antagonistic Two different Single drug molecules (A, B) act on the same STP (C) or the same sub-process (D) The resultant effect of DDI will be synergistic or antagonistic
10 Fundamental model of Pharmacodynamics DDIs - three-layered model - Medicine Signal Transduction Process (STP) Physiological Chain (PC) A C D (1) E Single drug molecules B (1) F Synergistic / Antagonistic Even when the targeting STPs are different (C, D), the pair (A & B) could be a possible DDI, (1) if the physiological responses are the same (E) (2) or included in the same physiological chain (E, F)
11 Fundamental model of Pharmacodynamics DDIs - three-layered model - Medicine Signal Transduction Process (STP) Physiological Chain (PC) C A D (2) E Single drug molecules B (2) F Synergistic / Antagonistic Even when the targeting STPs are different (C, D), the pair (A & B) could be a possible DDI, (1) if the physiological responses are the same (E) (2) or included in the same physiological chain (E, F)
12 Ontological representation (using HOZO editor)
13 Application to possible DDI reasoning
14 Framework to identify possible DDIs Based on the three-layered model [Rule]: i.e., there are at least three interaction points that might cause DDI A 1) pair Two drugs of two act drugs on the same will STP be identified as a possible DDI, if any 2) Two combination drugs act on the of same single sub-process drug molecules of STP of those drugs has the interaction that matches one of the 14 DDI types 3) The resultant physiological response is the same or included in the same physiological chain (PC) Five basic types of DDI DDI type STP Sub-process Physiological response Sub-types Type1 Same Different In the same PC Pro. / Inh. / Ant. Type2 Same Different Not related Pro. / Inh. / Ant. Type3 Same Same In the same PC Pro. / Inh. / Ant. Type4 Same Same Not related Pro. / Inh. / Ant. Type5 Different Different In the same PC Syn. / Ant.
15 Example domain & Experimental settings Drugs related to noradrenaline STP Noradrenaline is a representative among various chemical mediators Extracted 89 single drug molecules (SDM) related to noradrenaline STP from Japanese Drug Database (JAMES) Pharmacodynamics information for each SDM was manually analyzed and added into the ontology as subordinate classes. A pharmacology expert reviewed all the combinations of those SDMs, and extracted possible DDI pairs according to the extraction rule.
16 Experimental Result
17 Possible DDI pairs of 11/14 types Each pair has at lease one interaction point ( light gray cell ) that provides information about the reason why the pair was considered as a possible DDI in terms of pharmacodynamics mechanisms
18 Possible DDIs were not found for three sub-types (2i, 4p, 4i) For [Type 2i]: all SDMs acting on noradrenaline STP with inhibition effect have the same physiological response ( blood pressure decrease ) For [Type 4]: Very few cases BUT.. [Type4A] Same STP, same Sub-Process, but different Physiological responses Clonidine hydrochloride Mianserin hydrochloride Antagonistic DDI type STP Sub-process Physiological response Sub-types Type1 Same Different In the same PC Pro. / Inh. / Ant. Type2 Same Different Not related Pro. / Inh. / Ant. Type3 Same Same In the same PC Pro. / Inh. / Ant. Type4 Same Same Not related Pro. / Inh. / Ant. Type5 Different Different In the same PC Syn. / Ant.
19 Another interesting example: Type 5S These two SDMs don t share the same target STP and sub-process of STP. Physiological responses are not the same. But extracted as possible DDI (synergistic). Spironolactone Aldosterone STP Aldosterone receptor [SDM] [Target STP] [Target SubProcess] Propranolol hydrochloride Noradrenaline STP Beta1 adrenergic receptor [Physiological response] Excretion of sodium Decrease in blood volume Decrease in cardiac output Blood pressure decrease DDI type STP Sub-process Physiological response Sub-types Type5 Different Different In the same PC Syn. / Ant.
20 Discussion (1) 11 different types of possible DDIs were identified with supporting information of DDI mechanisms. Useful to understand contraindications distinguishability explanation capability [Type 3A] Non-selective beta blocker propranolol asthma drug salbutamol sulfate act on beta2-adrenergic receptor Comparison with SPCs in Japan 31% of all combinations were described There is no gold standard of true DDI pairs At least SPCs in Japan also have inconsistency (60%) For large-scale monitoring of drug safety (EU-ADR, etc.) Distinguishability and Explanation capability would be useful
21 Discussion (2) Comparison with preceding researches DrugBANK, PharmGKB, KEGG Contains a lot of information about pharmacodynamics pathways DDI information is not formally described (Natural language) Drug Interaction Ontology (DIO) Corresponding to the information of STP layer Fundamental framework for inferences of drug-biomolecule interactions like our approach Do not contain or formally describe the causal chains of physiological states Necessary for the detection of possible DDI pairs of Type 1, 3 and 5! DDI type STP Sub-process Physiological response Sub-types Type1 Same Different In the same PC Pro. / Inh. / Ant. Type3 Same Same In the same PC Pro. / Inh. / Ant. Type5 Different Different In the same PC Syn. / Ant.
22 Limitations & future tasks Limitations: Pharmacokinetics is out of the scope Tested on a limited domain Future tasks: To expand our ontology and to cover other types of DDIs. A new methodology to accumulate a lot of knowledge efficiently.
23 Acknowledgement This work is supported in part by Japan Society for the Promotion of Science (JSPS) through its Funding Program for World Leading Innovative R&D on Science and Technology (FIRST program) WG4
24 Thank you for attention! Questions & Discussion? Contact Takeshi IMAI, Ph.D The University of Tokyo Hospital, JAPAN
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