Abstract: A method for determining a next hypoxia-inducible factor prolyl hydroxylase inhibitor (HIF-PHI) dosage for a first patient using a patient HIF-PHI model is provided. The method includes obtaining population patient data indicating HIF-PHI dosages and hemoglobin measurements for the patients. Then, virtual patient avatars are generated based on the population patient data. Each of the virtual patient avatars indicates a set of personalized model parameters for a HIF-PHI model. A plurality of HIF-PHI models are determined for the virtual patient avatars. Using the HIF-PHI models, one or more HIF-PHI treatment schemes for administering the HIF-PHI dosages is determined. Subsequently, the HIF-PHI treatment schemes along with a hematocrit and/or hemoglobin concentration for a patient are used to determine a next HIF-PHI dosage for the patient, and the next HIF-PHI dosage is administered for the patient.

Abstract: A computing system for determining a systematic training strategy for the user is provided. The computing system includes a user device that uses one or more sensors to obtain partial pressure of oxygen (PO2) levels of a user over a period of time. The user device provides previous PO2 levels to a personalized erythropoiesis model generation computing platform. The computing platform obtains individualized user data for the user indicating or more previous hematocrit and/or hemoglobin measurements for the user. The computing platform determines an individualized erythropoiesis model for the user based on the one or more previous hematocrit and/or hemoglobin measurements and the previous PO2 information, and employs the individualized erythropoiesis model to determine predicted hematocrit and/or hemoglobin measurements. The computing platform performs one or more actions based on the one or more predicted hematocrit and/or hemoglobin measurements.

Abstract: The described technology may include treatment processes to increase the red blood cell (RBC) population of individuals, particularly chronic kidney disease (CKD) patients with renal anemia, by reducing an amount of Piezo1 chemical agonists in the blood of patients. In one embodiment, a method of treating a patient with renal anemia may include increasing RBC lifespan of an RBC population of the patient via reduction of a Piezo1 channel activation duration of at least a portion of the RBC population by reducing an amount of a target uremic compound in the blood of the patient, the target uremic compound having a form that prolongs the Piezo1 channel activation duration, wherein the amount of the target uremic compound may be reduced via selectively removing at least a portion of the target uremic compound from the blood of the patient. Other embodiments are described.

Abstract: The present invention relates to compounds of formula (I) and salts, stereoisomers, tautomers or N-oxides thereof that are useful as modulators of STING (Stimulator of Interferon Genes). The present invention further relates to the compounds of formula (I) for use as a medicament and to a pharmaceutical composition comprising said compounds.

Abstract: The present invention relates to compound-linker constructs and antibody-drug-conjugates of compounds of formula (I) that are useful as modulators of STING (Stimulator of Interferon Genes).

Abstract: Techniques are disclosed that reduce the computational complexity of PPM-based data compression through use of certain simplifying assumptions that permit faster search for a close-to-optimal PPM model than conventional techniques. The disclosed techniques permit the cost of the computationally-expensive model building task to be amortized over many compression/decompression cycles by maintaining a PersistentModel class, accessible to both the coder and decoder side of the system. This allows the computationally-expensive model building task to be performed only occasionally, as opposed to each time a message is coded. Furthermore, the model-building task is preferably scheduled to run at non-busy times, such that it minimizes user-perceptible service disruptions.

Abstract: Techniques are disclosed that reduce the computational complexity of PPM-based data compression through use of certain simplifying assumptions that permit faster search for a close-to-optimal PPM model than conventional techniques. The disclosed techniques permit the cost of the computationally-expensive model building task to be amortized over many compression/decompression cycles by maintaining a PersistentModel class, accessible to both the coder and decoder side of the system. This allows the computationally-expensive model building task to be performed only occasionally, as opposed to each time a message is coded. Furthermore, the model-building task is preferably scheduled to run at non-busy times, such that it minimizes user-perceptible service disruptions.