Abstract: In one aspect, a method is disclosed for presenting, on a computing device, a graphical user interface (GUI) of a therapeutic tool. The method includes presenting, in a first screen of the GUI, a design space for a protein for an application, where the design space includes a set of sequences, where each sequence contains a respective set of activities pertaining to the application. The method also includes receiving, via a graphical element in the first screen, a selection of one or more query parameters of the design space, and presenting, in a second screen of the GUI, a solution space that includes a subset of the set of sequences, where each sequence contains the respective set of activities, where the subset of the set of sequences is selected based on the one or more query parameters.

Abstract: In one aspect, a computer-implemented automated platform configured to use an artificial intelligence (AI) engine is disclosed and includes a reaction chamber configured to synthesize a sequence, detectors configured to monitor the synthesis of the sequence in the reaction chamber, and a computing device communicatively coupled to the detectors. The computing device receives measurements from the one or more detectors, wherein the measurements comprise a spectral profile at at least one coupling of at least one amino acid in the sequence, trains, using training data comprising the measurements, machine learning models to determine a synthesizing recipe that enables the sequence to be synthesized, wherein the synthesizing recipe comprises parameters used to synthesize the sequence, and controls, using the synthesizing recipe, the synthesis of the sequence in the reaction chamber.

Abstract: In one aspect, a method includes generating a design space for a peptide for an application. The generating includes identifying sequences for the peptide, and updating the sequences by determining, for each of the sequences, a respective set of activities pertaining to the application. The updating produces updated sequences each having updated respective activities. The method includes generating, based on the updated sequences, a solution space within the design space. The solution space includes a target subset of the updated sequences. The method includes performing, using a machine learning model to process the solution space, trials to identify a candidate drug compound that represents a sequence having a level of activity that exceeds a threshold level, and determining metrics pertaining to the machine learning model and a second machine learning model that performs the trials.

Abstract: In one aspect, a method is disclosed for presenting, on a computing device, a graphical user interface (GUI) of a therapeutic tool. The method includes presenting, in a first screen of the GUI, a design space for a protein for an application, where the design space includes a set of sequences, where each sequence contains a respective set of activities pertaining to the application. The method also includes receiving, via a graphical element in the first screen, a selection of one or more query parameters of the design space, and presenting, in a second screen of the GUI, a solution space that includes a subset of the set of sequences, where each sequence contains the respective set of activities, where the subset of the set of sequences is selected based on the one or more query parameters.

Abstract: In one aspect, a computer-implemented automated flow synthesis platform configured to use an artificial intelligence (AI) engine is disclosed and includes a reaction chamber configured to synthesize a sequence, detectors configured to monitor the synthesis of the sequence in the reaction chamber, wherein the synthesis uses an automated flow process, and a computing device communicatively coupled to the detectors. The computing device receives measurements from the one or more detectors, wherein the measurements comprise a spectral profile at each coupling of each amino acid in the sequence, trains, using training data comprising the measurements, machine learning models to determine a synthesizing recipe that enables the sequence to be synthesized, wherein the synthesizing recipe comprises parameters used during the automated flow process to synthesize the sequence, and controls, using the synthesizing recipe, the synthesis of the sequence in the reaction chamber.

Abstract: In one aspect, a method is disclosed for presenting, on a computing device, a graphical user interface (GUI) of a therapeutic tool. The method includes presenting, in a first screen of the GUI, a design space for a protein for an application, where the design space includes a set of sequences, where each sequence contains a respective set of activities pertaining to the application. The method also includes receiving, via a graphical element in the first screen, a selection of one or more query parameters of the design space, and presenting, in a second screen of the GUI, a solution space that includes a subset of the set of sequences, where each sequence contains the respective set of activities, where the subset of the set of sequences is selected based on the one or more query parameters.

Abstract: Methods are disclosed of making and using platforms for peptide synthesis and compositions thereof, such peptide-anchored resins or beads for use in solid-phase peptide synthesis. The platform includes a plurality of platform particles, which particles are insoluble carrier material particles (microparticles/nanoparticles) having a plurality of different linkers coupled to them. The plurality of linkers includes, in various combinations and combinations, (a) Fmoc-2,4-dimethoxy-4?-(carboxymethyloxy)-benzhydrylamine (Rink amide linker); (b) 4-Formyl-3-methoxy-phenoxyacetic acid; (c) 2-Hydroxy-5-dibenzosuberone; (d) 4-Hydroxymethylbenzoic acid (HMBA); (e) 4-Hydroxymethyl-phenoxyacetic acid (HMP linker); (f) 4-(Fmoc-hydrazino)-benzoic acid; (g) 4(4-(1-hydroxyethyl)-2-methoxy-5-nitrophenoxy)-butyric acid; and (h) Fmoc-Suberol (5-Fmoc-amino-2-carboxymethoxy-10,11-dihydro-5H-dibenzo[a,d] cycloheptene).

Abstract: In one aspect, a method is disclosed for presenting, on a computing device, a graphical user interface (GUI) of a therapeutic tool. The method includes presenting, in a first screen of the GUI, a design space for a protein for an application, where the design space includes a set of sequences, where each sequence contains a respective set of activities pertaining to the application. The method also includes receiving, via a graphical element in the first screen, a selection of one or more query parameters of the design space, and presenting, in a second screen of the GUI, a solution space that includes a subset of the set of sequences, where each sequence contains the respective set of activities, where the subset of the set of sequences is selected based on the one or more query parameters.

Abstract: In one aspect, a method is disclosed wherein an artificial intelligence (AI) enabled automated flow synthesis platform is configured to generate optimized synthesizing recipes which enable a sequence to be synthesized using an automated flow process. The method includes receiving a synthesizing recipe including parameters used during the automated flow process to synthesize the sequence, receiving spectral data from detectors monitoring the automated flow process in a reaction chamber, where the spectral data corresponds to a reaction point in the automated flow process, and determining, based on indicators associated with the spectral data, characteristics of a chemical reaction at the reaction point in the automated flow process. An artificial intelligence engine determines the chemical reaction. The method includes associating, based on the spectral data, the synthesizing recipe with the chemical reaction.

Abstract: In one aspect, a method is disclosed wherein an artificial intelligence (AI) enabled automated flow synthesis platform is configured to generate optimized synthesizing recipes which enable a sequence to be synthesized using an automated flow process. The method includes receiving a synthesizing recipe including parameters used during the automated flow process to synthesize the sequence, receiving spectral data from detectors monitoring the automated flow process in a reaction chamber, where the spectral data corresponds to a reaction point in the automated flow process, and determining, based on indicators associated with the spectral data, characteristics of a chemical reaction at the reaction point in the automated flow process. An artificial intelligence engine determines the chemical reaction. The method includes associating, based on the spectral data, the synthesizing recipe with the chemical reaction.

Abstract: In one aspect, a method is disclosed for presenting, on a computing device, a graphical user interface (GUI) of a therapeutic tool. The method includes presenting, in a first screen of the GUI, a design space for a protein for an application, where the design space includes a set of sequences, where each sequence contains a respective set of activities pertaining to the application. The method also includes receiving, via a graphical element in the first screen, a selection of one or more query parameters of the design space, and presenting, in a second screen of the GUI, a solution space that includes a subset of the set of sequences, where each sequence contains the respective set of activities, where the subset of the set of sequences is selected based on the one or more query parameters.

Abstract: In one aspect, a method is disclosed for presenting, on a computing device, a graphical user interface (GUI) of a therapeutic tool. The method includes presenting, in a first screen of the GUI, a design space for a protein for an application, where the design space includes a set of sequences, where each sequence contains a respective set of activities pertaining to the application. The method also includes receiving, via a graphical element in the first screen, a selection of one or more query parameters of the design space, and presenting, in a second screen of the GUI, a solution space that includes a subset of the set of sequences, where each sequence contains the respective set of activities, where the subset of the set of sequences is selected based on the one or more query parameters.

Abstract: In one aspect, a method includes generating a design space for a peptide for an application. The generating includes identifying sequences for the peptide, and updating the sequences by determining, for each of the sequences, a respective set of activities pertaining to the application. The updating produces updated sequences each having updated respective activities. The method includes generating, based on the updated sequences, a solution space within the design space. The solution space includes a target subset of the updated sequences. The method includes performing, using a machine learning model to process the solution space, trials to identify a candidate drug compound that represents a sequence having a level of activity that exceeds a threshold level, and determining metrics pertaining to the machine learning model and a second machine learning model that performs the trials.

Abstract: In one aspect, a method is disclosed for using dialects to generate candidate drug compounds. The dialects describe sequences of the candidate drug compounds and activities associated with the sequences. The method includes receiving a data set, training, using the data set, first layers of a machine learning model to determine relationships of components of a portion of a string described by a first dialect. The components pertain to amino acids associated with first activity level information of the sequences. The method includes training, using the data set and the portion of the string, a final layer to generate a remainder of the string. The remainder pertains to second activity level information of the sequences. The method includes generating, using the first and final layer, the string comprising the portion and the remainder. The string represents a candidate drug compound.

Abstract: In one aspect, a computer-implemented automated flow synthesis platform configured to use an artificial intelligence (AI) engine is disclosed and includes a reaction chamber configured to synthesize a sequence, detectors configured to monitor the synthesis of the sequence in the reaction chamber, wherein the synthesis uses an automated flow process, and a computing device communicatively coupled to the detectors. The computing device receives measurements from the one or more detectors, wherein the measurements comprise a spectral profile at each coupling of each amino acid in the sequence, trains, using training data comprising the measurements, machine learning models to determine a synthesizing recipe that enables the sequence to be synthesized, wherein the synthesizing recipe comprises parameters used during the automated flow process to synthesize the sequence, and controls, using the synthesizing recipe, the synthesis of the sequence in the reaction chamber.

Abstract: In one aspect, a computer-implemented automated flow synthesis platform configured to use an artificial intelligence (AI) engine is disclosed and includes a reaction chamber configured to synthesize a sequence, detectors configured to monitor the synthesis of the sequence in the reaction chamber, wherein the synthesis uses an automated flow process, and a computing device communicatively coupled to the detectors. The computing device receives measurements from the one or more detectors, wherein the measurements comprise a spectral profile at each coupling of each amino acid in the sequence, trains, using training data comprising the measurements, machine learning models to determine a synthesizing recipe that enables the sequence to be synthesized, wherein the synthesizing recipe comprises parameters used during the automated flow process to synthesize the sequence, and controls, using the synthesizing recipe, the synthesis of the sequence in the reaction chamber.

Abstract: In one aspect, a method is disclosed wherein an artificial intelligence (AI) enabled automated flow synthesis platform is configured to generate optimized synthesizing recipes which enable a sequence to be synthesized using an automated flow process. The method includes receiving a synthesizing recipe including parameters used during the automated flow process to synthesize the sequence, receiving spectral data from detectors monitoring the automated flow process in a reaction chamber, where the spectral data corresponds to a reaction point in the automated flow process, and determining, based on indicators associated with the spectral data, characteristics of a chemical reaction at the reaction point in the automated flow process. An artificial intelligence engine determines the chemical reaction. The method includes associating, based on the spectral data, the synthesizing recipe with the chemical reaction.

Abstract: An artificial intelligence engine architecture for generating candidate drugs is disclosed. In one embodiment, a method includes generating, via a creator module, a candidate drug compound including a sequence of a candidate drug compound, including the candidate drug compound as a node in a knowledge graph; generating, via a descriptor module, a description of the candidate drug compound at the node in the knowledge graph, wherein the description comprises drug compound structural information, drug compound activity information, and drug compound semantic information; based on the description, performing, via a scientist module, a benchmark analysis of a parameter of the creator module; and modifying, based on the benchmark analysis, the creator module to change the parameter in a desired way during a subsequent benchmark analysis.

Abstract: In one aspect, a method is disclosed for presenting, on a computing device, a graphical user interface (GUI) of a therapeutic tool. The method includes presenting, in a first screen of the GUI, a design space for a protein for an application, where the design space includes a set of sequences, where each sequence contains a respective set of activities pertaining to the application. The method also includes receiving, via a graphical element in the first screen, a selection of one or more query parameters of the design space, and presenting, in a second screen of the GUI, a solution space that includes a subset of the set of sequences, where each sequence contains the respective set of activities, where the subset of the set of sequences is selected based on the one or more query parameters.

Abstract: In one aspect, a method includes generating a design space for a peptide for an application. The generating includes identifying sequences for the peptide, and updating the sequences by determining, for each of the sequences, a respective set of activities pertaining to the application. The updating produces updated sequences each having updated respective activities. The method includes generating, based on the updated sequences, a solution space within the design space. The solution space includes a target subset of the updated sequences. The method includes performing, using a machine learning model to process the solution space, trials to identify a candidate drug compound that represents a sequence having a level of activity that exceeds a threshold level, and transmitting information describing the candidate drug compound to a computing device.