CPC field-specific training

Transcription

1 CPC field-specific training G06F19/10 Bioinformatics, G06F19/70 Chemoinformatics, C40B30/02, C40B50/02 In silico Combinatorial Chemistry, G16H Healthcare Informatics Przemyslaw Godzina Examiner, European Patent Office June 2018

2 About the speaker Name: Przemyslaw Godzina Nationality: Polish Education: PhD in Chemistry (Combinatorial Chemistry of nucleic acids); post-doc in Genetic Chemistry EPO: 15+ yrs. (Computational Chemistry 11 yrs., Bioinformatics 9 yrs., Healthcare Informatics 4 yrs., Classification Board 2 yrs.) European Patent Office 2

3 Agenda general overview Introduction Schemes and specific terminology Classification rules Examples European Patent Office 3

4 Introduction Historical perspective and future developments Definitions Interdisciplinary character European Patent Office 4

5 Introduction Historical perspective G06F19/00 created in the late 90's in response to the need to classify documents dedicated to specific applications of computers At the same time, a subgroup for healthcare/medical informatics was created Followed, in subsequent years, by the creation of subgroups for bioinformatics and chemoinformatics-related documents In 2011 bioinformatics appeared in the IPC under G06F19/10 In 2018 healthcare informatics was introduced into the IPC under G16H European Patent Office 5

6 Introduction Future developments (1) Bioinformatics and chemoinformatics will follow the transfer of healthcare informatics to be placed under G16B and G16C, respectively G06F19/00 to be deleted C40B30/02 and C40B50/02 to be deleted; documents to be manually reclassified into corresponding subgroups within bioinformatics or chemoinformatics schemes Possibly new application fields to be placed under G16 European Patent Office 6

7 Introduction Future developments (2) G16 new class in IPC and CPC created G06F19/10, C40B30/02, C40B50/02 Bioinformatics in IPC and CPC G06F19/70, C40B30/02, C40B50/02 Chemoinformatics in CPC G06F19/30 Medical Informatics in CPC G16B Bioinformatics in IPC and CPC to be created G16C Computational Chemistry in IPC and CPC to be created G16H Healthcare Informatics in IPC and CPC created G16M? Computational Materials Science European Patent Office 7

8 Introduction Definitions Bioinformatics methods or systems for genetic or protein-related data processing in computational molecular biology Chemoinformatics/Cheminformatics/Computational Chemistry data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds In silico Combinatorial Chemistry computational methods of creating and screening combinatorial libraries Healthcare Informatics Information and Communication Technology [ICT] specially adapted for the handling or processing of medical or healthcare data European Patent Office 8

9 Introduction Interdisciplinary character ~ G06F19/10 C40B30/02 C40B50/02 G16H ~ G06F19/70 ~ C40B30/02 C40B50/02 ~ 800 European Patent Office 9

10 Agenda general overview Introduction Schemes and specific terminology Classification rules Examples European Patent Office 10

11 Schemes and specific terminology Scheme under G06F19/00 G G06 G06F G06F19/00 G06F19/10. G06F19/70. PHYSICS COMPUTING; CALCULATING; COUNTING ELECTRIC DIGITAL DATA PROCESSING Digital computing or data processing equipment or methods, specially adapted for specific applications Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds European Patent Office 11

12 Schemes and specific terminology Scheme Bioinformatics (1) G06F19/10. G06F19/12.. G06F19/14.. G06F19/16.. Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks for phylogeny or evolution, e.g. evolutionarily conserved regions determination or phylogenetic tree construction for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures European Patent Office 12

13 Schemes and specific terminology Scheme Bioinformatics (2) G06F19/18.. G06F19/20.. G06F19/22.. for functional genomics or proteomics, e.g. genotypephenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, proteinprotein interactions or protein-nucleic acid interactions for hybridisation or gene expression, e.g. microarrays, sequencing by hybridisation, normalisation, profiling, noise correction models, expression ratio estimation, probe design or probe optimisation for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or Single- Nucleotide Polymorphism [SNP] discovery or sequence alignment European Patent Office 13

14 Schemes and specific terminology Scheme Bioinformatics (3) G06F19/24.. for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification G06F19/26.. for data visualisation, e.g. graphics generation, display of maps or networks or other visual representations G06F19/28.. for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures European Patent Office 14

15 Schemes and specific terminology Specific terminology in Bioinformatics (1) Drug targeting drug design strategy aiming at optimising the properties of a medicinal compound, based on the 3-dimensional structure of a target, for delivery to a particular tissue or organ in the body Functional genomics experimental analyses aiming at assessing the function of genes in determining traits, physiology and/or development of an organism, making use of computational and high-throughput technologies Proteomics large-scale study of the functions of proteins and their interactions with other molecular entities in a biological system Gene expression process by which proteins are made or transcribed from the instructions encoded in DNA European Patent Office 15

16 Schemes and specific terminology Specific terminology in Bioinformatics (2) Gene expression profiling determination of the pattern of genes expressed, i.e. transcribed, under specific circumstances or in a specific cell line Microarray plurality of nucleic acid probes attached to a substrate, which form an ordered pattern Genome annotation allocation of functions to individual genes in the genome Genotype genetic makeup or profile of an organism with respect to a trait Genotyping analysis of an organism's genotype Haplotype set of one or more polymorphisms (sequence variations) that may be found at a particular genetic location on the same chromosome Phylogenetic tree tree-like graphical representation of phylogenetic relationships European Patent Office 16

17 Schemes and specific terminology Specific terminology in Bioinformatics (3) Phylogeny reconstruction of an evolutionary development and history of a species or higher taxonomic grouping of organisms; typically represented as a phylogenetic tree; methods for creating phylogenetic trees Taxonomy classification of organisms to show their evolutionary relationships to other organisms Sequencing by hybridisation DNA sequencing technique in which an array of short sequences of nucleotides is brought in contact with a solution of a target DNA sequence, a biochemical method determines a subset of probes that bind to the target sequence and a combinatorial method is then used to reconstruct the DNA sequence from the spectrum SNP single nucleotide polymorphism: a DNA sequence variation that involves a change in a single nucleotide and is commonly present in a part of a population European Patent Office 17

18 Schemes and specific terminology Specific terminology in Bioinformatics (4) Systems biology simulation and mathematical modelling of relationships and interactions between molecular entities in subcellular systems integrating genetic and/or protein-related data to describe the dynamic behaviour of, for example, proteinprotein/protein-ligand interactions, regulatory networks and metabolic networks Programming tools computer software to assist programming procedures European Patent Office 18

19 Schemes and specific terminology Scheme Chemoinformatics (1) G06F19/70. Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds G06F19/701.. for molecular modelling, e.g. calculation and theoretical details of quantum mechanics, molecular mechanics, molecular dynamics, Monte Carlo methods, conformational analysis or the like G06F19/702.. for analysis and planning of chemical reactions and syntheses, e.g. synthesis design, reaction prediction, mechanism elucidation G06F19/703.. for computer-assisted identification of chemical compounds or molecular structures, e.g. computerassisted structure elucidation [CASE] systems European Patent Office 19

20 Schemes and specific terminology Scheme Chemoinformatics (2) G06F19/704.. for prediction of properties of compounds, e.g. calculating and selecting molecular descriptors, details related to the development of SAR/QSAR/QSPR models, ADME/Tox models or PK/PD models G06F19/705.. for database search of chemical structures, e.g. full structure search, substructure search, similarity search, pharmacophore search, 3D structure search G06F19/706.. for drug design with the emphasis on a therapeutic agent, e.g. ligand-biological target interactions, pharmacophore generation European Patent Office 20

21 Schemes and specific terminology Scheme Chemoinformatics (3) G06F19/707.. using machine learning, data mining or chemometrics, e.g. pattern recognition, knowledge discovery, rule extraction, correlation, clustering or classification, chemical name to structure conversion G06F19/708.. for data visualisation, e.g. molecular structure representation, graphics generation, display of maps or networks or other visual representations G06F19/709.. for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures European Patent Office 21

22 Schemes and specific terminology Specific terminology in Chemoinformatics (1) Quantum mechanics a fundamental theory in physics which describes nature at the smallest scales of energy levels of atoms and subatomic particles Molecular mechanics classical mechanics used to model molecular systems Molecular dynamics a computer simulation method for studying the physical movements of atoms and molecules Molecular descriptor final result of a logic and mathematical procedure which transforms chemical information encoded within a symbolic representation of a molecule into a useful number or the result of some standardized experiment. European Patent Office 22

23 Schemes and specific terminology Specific terminology in Chemoinformatics (2) Quantitative/Qualitative Structure-Activity/Property Relationship (QSAR/QSPR) regression or classification models used to correlate chemical structures with a certain property of a molecule Absorption, Distribution, Metabolism, Excretion and Toxicity (ADME/Tox) studies which are conducted during the discovery, drug lead optimisation, and preclinical development phases to obtain data characterising drug candidates and to predict their fate after administration into the human body Pharmacokinetic/pharmacodynamic (PK/PD) modelling a mathematical technique combining the knowledge of pharmacokinetics and pharmacodynamics for predicting the effect and efficacy of drug dosing over time European Patent Office 23

24 Schemes and specific terminology Specific terminology in Chemoinformatics (3) Pharmacophore an ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target and to trigger (or block) its biological response Ligand (in biochemistry and pharmacology) a substance that forms a complex with a biomolecule to serve a biological purpose Drug lead (in drug discovery) a chemical compound that has pharmacological or biological activity likely to be therapeutically useful, but may have suboptimal structure that requires modification to fit better to the target molecule, e.g. a protein; drug leads are potentially followed by back-up compounds Chemometrics the science of extracting information from chemical systems using multivariate statistics, applied mathematics and computer science European Patent Office 24

25 Schemes and specific terminology Scheme In silico Combinatorial Chemistry C C40 C40B C40B30/00 C40B30/02. C40B50/00 C40B50/02. CHEMISTRY; METALLURGY COMBINATORIAL TECHNOLOGY COMBINATORIAL CHEMISTRY; LIBRARIES, e.g. CHEMICAL LIBRARIES, IN SILICO LIBRARIES Methods of screening libraries In silico screening Methods of creating libraries, e.g. combinatorial synthesis In silico or mathematical conception of libraries European Patent Office 25

26 Schemes and specific terminology Specific terminology in in silico Comb. Chem. Combinatorial library regression or classification models used to correlate chemical structures with a certain property of a molecule In silico performed on a computer/via computer simulation Virtual chemical/compound library descriptions of all of the structures that might be produced by specified transformations involving specified reagents In silico/virtual screening a computational technique used to select, from a pull of candidate molecules, a subset of compounds for experimental validation European Patent Office 26

27 Schemes and specific terminology Scheme Healthcare Informatics (1) G G16 G16H G16H10/00 G16H15/00 PHYSICS INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ICT specially adapted for the handling or processing of patient-related medical or healthcare data ICT specially adapted for medical reports, e.g. generation or transmission thereof European Patent Office 27

28 Schemes and specific terminology Scheme Healthcare Informatics (2) G16H20/00 G16H30/00 G16H40/00 G16H50/00 ICT specially adapted for therapies or healthimproving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance ICT specially adapted for the handling or processing of medical images ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics European Patent Office 28

29 Schemes and specific terminology Scheme Healthcare Informatics (3) G16H70/00 ICT specially adapted for the handling or processing of medical references G16H80/00 ICT specially adapted for facilitating communication between medical practitioners, e.g. for collaborative diagnosis, therapy or health monitoring European Patent Office 29

30 Schemes and specific terminology Specific terminology in Healthcare Informatics Telemedicine the remote delivery of health care services such as health assessment or consultations, over the telecommunications infrastructure Clinical trial research studies that explore whether a medical strategy, treatment or device is safe and effective for humans Medical expert system complex computer programme that emulates clinical reasoning; it consists of a knowledge base in which doctors' expertise is encoded and an "inference engine" which manipulates that knowledge European Patent Office 30

31 Agenda general overview Introduction Schemes and specific terminology Classification rules Examples European Patent Office 31

32 Classification rules Chemoinformatics vs. Bioinformatics (1) Lead Drug Protein Gene Chemoinformatics Bioinformatics European Patent Office 32

33 Classification rules Chemoinformatics vs. Bioinformatics (2) Algorithms Applications Type of molecule European Patent Office 33

34 Classification rules Neighbouring fields Biometric patterns based G06Q50/24 on physiological signals, e.g. heartbeat, blood flow Patient record management NO LONGER USED Signal processing or signal transmission associated to diagnostic measurements, e.g. signal waveform analysis A61B5/00 G06K9/00939 G16H C12Q1/68 C40B30/02 C40B50/02 G06F19/10 G06F19/70 C12Q1/6827 Hybridisation assays for detection of mutation or polymorphism C12Q1/6837 Enzymatic or biochemical coupling of nucleic acids to a solid phase using probe arrays or probe chips C12Q1/686 Polymerase chain reaction [PCR] C12Q1/6869 Methods for sequencing involving mass spectrometry C12Q1/6874 Methods for sequencing involving nucleic acid arrays, e.g. sequencing by hybridisation H01J49/0036 Handling of data generated during a mass spectrometry measurement G06F17/30 Information retrieval; Database structures Manufacture of microarrays, DNA chips B01J19/0046 C40B30/02 C40B50/02 G01N30/86 Analysing signal from column chromatography G06F17/50 Methods of protein analysis involving mass spectrometry G01N33/6848 G01N2201/12 Spectroscopy signal processing G005B15/02 Systems controlled by a computer Computer-aided design European Patent Office 34

35 Classification rules G06F19/10 G06F19/70 G16H C40B30/02, C40B50/02 G06F19/24 for machine learning, data mining or biostatistics Nucleic acids, oligonucleotides, nucleosides, nucleotides, proteins, peptides, amino acids Any other type of molecule Documents dealing with molecular level type of data (molecular structures, mechanisms of molecular interactions and reactions, etc.) are not classified in G16H at least as CCI For the time being no distinction between different types of molecules, i.e. nucleic acids, proteins and peptides on one hand and any other type of molecule on the other hand Corresponding subgroups G06F19/26 Corresponding subgroups G06F19/708 G06F19/28 Corresponding subgroups G06F19/709 G06F19/16 Major overlap between Bio- and Chemoinformatics G06F19/707 for machine learning, data mining or chemometrics G06F19/706 European Patent Office 35

36 Agenda general overview Introduction Schemes and specific terminology Classification rules Examples European Patent Office 36

37 Examples Example (1.1) A method for designing an inhibitor that covalently binds a target polypeptide, comprising: A) providing a structural model of a reversible inhibitor bound to a binding site in a target polypeptide, wherein the reversible inhibitor makes non-covalent contacts with the binding site; B) identifying a Cys residue in the binding site of the target polypeptide that is adjacent to the reversible inhibitor when the reversible inhibitor is bound to the binding site; C) producing structural models of candidate inhibitors that covalently bind the target polypeptide, wherein each candidate inhibitor contains a warhead that is bonded to a substitutable position of the reversible inhibitor, the warhead comprising a reactive chemical functionality and optionally a linker that positions the reactive chemical functionality within bonding distance of the Cys residue in the binding site of the target polypeptide; European Patent Office 37

38 Examples Example (1.2) D) determining the substitutable positions of the reversible inhibitor that result in the reactive chemical functionality of the warhead being within bonding distance of the Cys residue in the binding site of the target polypeptide when the candidate inhibitor is bound to the binding site; G06F19/706 CCI G06F19/16 CCA E) for a candidate inhibitor that contains a warhead that is within bonding distance of the Cys residue in the binding site of the target polypeptide when the candidate inhibitor is bound to the binding site, forming a covalent bond between the sulfur atom of the Cys residue in the binding site and the reactive chemical functionality of the warhead when the candidate inhibitor is bound to the binding site, wherein a covalent bond length of less than about 2Å indicates that the candidate inhibitor is an inhibitor that covalently binds a target polypeptide. European Patent Office 38

39 Examples Example (2.1) A method for estimating the difference between binding free energies of molecules, said method carried out on a computer and comprising: carrying out a molecular dynamics simulation or a Monte Carlo simulation on a large molecule and at least one small molecule, wherein the small molecule is not an unphysical reference state, to obtain multiple conformations of said large and small molecules in a binding environment of the large molecule; determining an energy of the small molecule in said binding environment for said conformations; replacing one or more atoms of said small molecule with one or more different atoms for each of said conformations, to obtain a modified small molecule in said binding environment; European Patent Office 39

40 Examples Example (2.2) determining an energy of the modified small molecule in said binding environment for said conformations, wherein a molecular dynamics simulation or Monte Carlo simulation is not carried out on said modified small molecule; and G06F19/704 CCI G06F19/701, 19/706, 19/16 CCA carrying out a single step perturbation calculation using said energies of the small and modified small molecules, to obtain the estimated difference between the binding free energies of said small and modified small molecules to said large molecule. European Patent Office 40

41 Examples Example (3.1) A method of identifying a variant of an antibody with enhanced antigen binding affinity, the method comprising: (a) determining a three-dimensional representation of an antibodyantigen interface of a first antibody, (b) conformationally sampling point mutations of amino acid residues of the antibody at the antibody-antigen interface, (c) selecting the point mutations of step (b) that are conformationally allowed, European Patent Office 41

42 Examples Example (3.2) (d) selecting the point mutations of step (c) that have both a Boltzmann averaged predictor based on a change of a change of a free energy of binding (AAG*) of less than zero kcal/mol and a Boltzmann averaged predictor based on only a change of a change of the polar component of a free energy of binding (ΔΔΕ pοl *) of less than zero kcal/mol, and G06F19/16 CCI C40B30/02, 50/02 CCA (e) creating a focused library of antibodies containing at least one point mutation from the point mutations of step (d), (f) screening the antibodies of step (e) for enhanced antigen-binding affinity in vitro; and (g) selecting an antibody of step (f) having enhanced binding affinity relative to the first antibody, thereby identifying a variant of an antibody with enhanced antigen binding affinity. European Patent Office 42

43 Examples Example (4) A method of dynamically adjusting personalized health and wellness programs, comprising the steps of: G16H10/60, 15/00, 50/30 CCI developing a health and wellness program for a user based on a user health profile; collecting user activity pertaining to the user's participation in the health and wellness program from one or more wireless health devices; evaluating the user's health based on the collected user activity; and adjusting the health and wellness program based on the evaluation of the user's health. European Patent Office 43

44 Examples Example (5.1) A method of identifying a solid epithelial tumor cancer patient as being likely to benefit from treatment with a therapeutic agent or a combination of therapeutic agents targeting agonists of the receptors, receptors or proteins involved in MAPK (mitogen-activated protein kinase) pathways or the PKC (protein kinase C) pathway upstream from or at Akt or ERK/JNK/p38 or PKC or not likely to benefit from treatment with the therapeutic agent or the combination of therapeutic agents, comprising the steps of: a) obtaining a mass spectrum from a blood-based sample from the solid epithelial tumor cancer patient; b) performing one or more predefined pre-processing steps on the mass spectrum obtained in step a); European Patent Office 44

45 Examples Example (5.2) c) obtaining integrated intensity values of selected features in said spectrum at one or more predefined m/z ranges after the preprocessing steps on the mass spectrum in step b) have been performed; G06F19/707 CCI G06F19/703 CCA d) using the values obtained in step c) in classification algorithm using a training set comprising class-labeled spectra produced from bloodbased samples from other solid tumor patients to identify the patient as being either likely or not likely to benefit from treatment with the therapeutic agent or a combination of therapeutic agents. European Patent Office 45

46 Examples Example (6.1) A method for determining a chemometric model of near infrared spectroscopic (NIRS) data to identify a characteristic of interest in a plant sample, the method comprising: providing a plant sample to be analysed; acquiring NIRS data from the plant sample; providing a computer readable storage medium comprising a database comprising a plurality of chemometric models of NIRS data, wherein the NIRS data comprises information regarding the characteristic of interest; selecting parameters for use in each of the plurality of chemometric models; European Patent Office 46

47 Examples Example (6.2) utilizing each of the plurality of chemometric models to determine a relationship between the NIRS data acquired from the plant sample and the characteristic of interest; and G06F19/707 CCI G06F19/703 CCA determining the chemometric model that most closely relates the NIRS data acquired from the plant sample and the characteristic of interest, wherein the chemometric model that most closely relates the NIRS data acquired from the plant sample and the characteristic of interest identifies the characteristic of interest. European Patent Office 47

48 Examples Example (7) A method of estimating a pose of a ligand in a receptor comprising: identifying all possible atom pairs of protein-ligand complexes in a given G06F19/706, G06F19/16 CCI G06F19/709 CCA configuration space for a system that comprises proteins; creating a first database and a second database; where the first database comprises associated pairwise distant dependent energies and where the second database comprises all probabilities that include how the atom pairs can combine; combining the first database with the second database via statistical mechanics to accurately estimate binding free energies as well as the pose of the ligand in the receptor; and selecting a protein-ligand complex for further study. European Patent Office 48

49 Examples Example (8) A method for determining the composition of a material from a petroleum stream, comprising: G06F19/704 CCI obtaining a reference model of composition (MoC) for the material having a boiling point above about 1000 F at atmospheric pressure, the reference MoC including a combination of molecular lumps having determined reference percent for each of the molecular lumps; and reconciling, using at least one computer processor, the reference MoC to match at least one selected target property of the material to obtain a reconciled MoC representative of the composition of the material. European Patent Office 49

50 Examples Example (9) A computer-implemented method for generating a library of polypeptides or antibodies, the method comprising: C40B50/02 CCI obtaining a first amino acid sequence of a complementarity determining region (CDR) associated with a heavy chain and a second amino acid sequence of a CDR associated with a light chain from a database of CDR sequences; obtaining one or more variable heavy (VH) and variable light (VL) structural framework (VH/VL) pairs, wherein each of said pairs having one or more predetermined developability properties that facilitate for screening antibodies; and analysing said amino acid sequences and said VH/VL pairs with the use of a macromolecular algorithmic unit to generate one or more structures. European Patent Office 50

51 Examples Example (10.1) A system for facilitating mobile telemedicine for a suspected stroke case comprising: a scheduling module to: project an amount of time for a vehicle transporting a patient to arrive at a specified hospital; compare the projected amount of time to a threshold; and send the comparison to a communication module; and a communication module to: in response to the comparison, initiating, with a mobile computing device, a prehospital telemedicine videoconference with an evaluation device when the projected amount of time exceeds the threshold; European Patent Office 51

52 Examples Example (10.2) receive, from the evaluation device, a set of specified symptoms of a stroke and information indicative as to whether the patient is exhibiting symptoms of a stroke, using the prehospital mobile telemedicine videoconference; and G16H80/00 CCI generate a medical alert, the medical alert including patient information and the information indicative as to whether the patient is exhibiting symptoms of a stroke. European Patent Office 52

53 Thank you for your attention! European Patent Office 53