AIMC Topic: Immunosuppressive Agents

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Improved Arterial Stiffness Indices 3 and 6 Months after Living-donor Renal Transplantation.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Arterial stiffness is a non-traditional risk factor of cardiovascular disease and may explain part of the excess cardiovascular risk in chronic kidney disease patients. Successful renal transplantation (RT) may restore renal function and improve seve...

Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease.

Clinical pharmacology and therapeutics
Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLMs) like Bidir...

Mycophenolic Acid Exposure Prediction Using Machine Learning.

Clinical pharmacology and therapeutics
Therapeutic drug monitoring of mycophenolic acid (MPA) based on area under the curve (AUC) is well-established and machine learning (ML) approaches could help to estimate AUC. The aim of this work is to estimate the AUC of MPA in organ transplant pat...

Estimation of drug exposure by machine learning based on simulations from published pharmacokinetic models: The example of tacrolimus.

Pharmacological research
We previously demonstrated that Machine learning (ML) algorithms can accurately estimate drug area under the curve (AUC) of tacrolimus or mycophenolate mofetil (MMF) based on limited information, as well as or even better than maximum a posteriori Ba...

Application Prospect of Artificial Intelligence in Rehabilitation and Management of Myasthenia Gravis.

BioMed research international
Myasthenia gravis (MG) is a chronic autoimmune disease of the nervous system, which is still incurable. In recent years, with the progress of immunosuppressive and supportive treatment, the therapeutic effect of MG in the acute stage is satisfactory,...

Tacrolimus Exposure Prediction Using Machine Learning.

Clinical pharmacology and therapeutics
The aim of this work is to estimate the area-under the blood concentration curve of tacrolimus (TAC) following b.i.d. or q.d. dosing in organ transplant patients, using Xgboost machine learning (ML) models. A total of 4,997 and 1,452 TAC interdose ar...

Machine learning predicts stem cell transplant response in severe scleroderma.

Annals of the rheumatic diseases
OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT...

Patterns of 1,748 Unique Human Alloimmune Responses Seen by Simple Machine Learning Algorithms.

Frontiers in immunology
Allele specific antibody response against the polymorphic system of HLA is the allogeneic response marker determining the immunological risk for graft acceptance before and after organ transplantation and therefore routinely studied during the patien...

Building the drug-GO function network to screen significant candidate drugs for myasthenia gravis.

PloS one
Myasthenia gravis (MG) is an autoimmune disease. In recent years, considerable evidence has indicated that Gene Ontology (GO) functions, especially GO-biological processes, have important effects on the mechanisms and treatments of different diseases...