Results for “fda-drug-labels”

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Access ClinPGx pharmacogenomics data (the successor to PharmGKB) to query gene-drug interactions, CPIC/DPWG dosing guidelines, drug labels, and pharmacogene records. Use when interpreting pharmacogenes (CYP2D6, CYP2C19, TPMT, DPYD, SLCO1B1), looking up genotype-guided drug dosing, checking PGx drug-safety associations (e.g. HLA-B*57:01 and abacavir), or supporting precision medicine and clinical pharmacogenomics decisions. For star-allele definitions/frequencies see PharmVar; for germline/somatic variant pathogenicity see alterlab-clinvar. Part of the AlterLab Academic Skills suite.

Drafts U.S. HACCP plans for food production under FDA or USDA regimes. Triggers on requests involving HACCP plans, food safety plans, hazard analysis, critical control points, FSMA compliance, seafood HACCP (21 CFR 123), or meat/poultry HACCP (9 CFR 417).

Therapeutics Data Commons. Conjuntos de dados prontos para IA em descoberta de drogas (ADME, toxicidade, DTI), benchmarks, divisões de scaffold, oráculos moleculares, para ML terapêutico e predição farmacológica.

Maps the US federal privacy landscape including sectoral laws (HIPAA, GLBA, FERPA, COPPA, FCRA, ECPA, VPPA), FTC Section 5 enforcement, proposed federal comprehensive legislation, and the interaction between federal and state privacy regimes. Keywords: federal privacy, HIPAA, GLBA, FERPA, COPPA, FCRA, FTC, sectoral, preemption.

Use when you need to annotate BAM alignments with a two-character tag based on overlaps with BED, GFF, or VCF annotation files, such as labeling reads by feature class or interval source.

Applies medicinal-chemistry filters with the medchem library — drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, and molecular complexity metrics for compound prioritization and library cleanup. Use when filtering or triaging a compound library, flagging PAINS or reactive groups, or assessing drug-likeness of candidate molecules. Part of the AlterLab Academic Skills suite.

Recommends weight‑losing and weight‑neutral medications as first‑ and second‑line agents for managing overweight/obese patients with type 2 diabetes. Triggers include when a clinician asks, 'Which diabetes medications will not worsen weight in this obese patient?' or 'Should I avoid sulfonylureas in this patient with T2DM and obesity due to weight gain risk?'

Guides dose escalation for obesity pharmacotherapy based on efficacy and tolerability while staying within approved upper dose limits. Triggers include clinician questions like "How should I titrate naltrexone/bupropion if the starting dose is tolerated?" or "What is the maximum liraglutide dose I can use?"

Form Labels and Helper Text

Apply medicinal chemistry filters for compound triage: drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and a custom query language for library filtering.

Implements 42 CFR Part 2 protections for substance use disorder patient records. Covers written consent requirements stricter than HIPAA, re-disclosure prohibition, court order procedures, qualified service organization agreements, and 2024 amendments aligning Part 2 with HIPAA. Keywords: 42 CFR Part 2, substance use disorder, SUD records, re-disclosure, consent, Part 2 amendments.

Recommends ACE inhibitors, ARBs, or calcium channel blockers as first-line hypertension therapy rather than β‑adrenergic blockers in obese patients with type 2 diabetes. Triggers include when a clinician asks, 'What antihypertensive should I start for this obese patient with T2DM to avoid weight gain?' or 'Should I avoid β‑blockers in this patient with diabetes and hypertension?'

Bedside prescribing reference for Bemdec (bempedoic acid / NEXLETOL) — indication check, dose, statin co-prescribing safety caps, monitoring plan, warnings for hyperuricemia and tendon rupture, and special population guidance. Use when a clinician asks "can I start bempedoic acid", "Bemdec indication", "is bempedoic acid safe with my statin", "patient on Nexletol has joint pain or high uric acid", "bempedoic acid in CKD or liver disease or pregnancy", or any prescribing or monitoring question about bempedoic acid.

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores, drug sensitivity data, and gene effect profiles to identify cancer-specific vulnerabilities, synthetic lethal interactions, and validate oncology drug targets.

Access the Human Metabolome Database (HMDB, 220K+ metabolites), searching by name, HMDB ID, or structure to retrieve chemical properties, biomarker data, NMR/MS reference spectra, and associated pathways. Use when identifying a human metabolite, looking up its biomarker or disease associations, matching NMR/MS spectra, or running metabolomics annotation. Part of the AlterLab Academic Skills suite.

Save the current diagnosis state to disk for cross-session recall, including conclusions, rejected directions, and next steps.

Assess pharmacotherapy eligibility based on BMI/comorbidity

Advises assessing efficacy and safety at least monthly for the first 3 months, then at least every 3 months for all patients prescribed weight‑loss medications. Triggers include clinician questions such as “How often should I check progress after starting orlistat?” or “What is the follow‑up schedule for a patient on liraglutide?”.

Guides comorbidity-stratified selection of initial and further glucose-lowering medicines for adults with type 2 diabetes using the NICE NG28 (2026) framework, covering six clinical profiles: no relevant comorbidity, heart failure, atherosclerotic cardiovascular disease, early onset, obesity, chronic kidney disease, and frailty.

Select oral and injectable glucose-lowering agents for a newly diagnosed patient with type 2 diabetes using a compelling-indication hierarchy (heart failure → ASCVD → DKD → obesity) followed by glucose-pattern matching. Incorporates modern GLP-1 receptor agonists — Ozempic (semaglutide SC, T2D), Mounjaro (tirzepatide), and Wegovy/Noveltreat (semaglutide 2.4 mg, obesity). Use when a clinician asks "what drug to start for newly diagnosed T2D", "which OAD to use", "first-line diabetes medication", "SGLT2i vs GLP-1 in new T2D", or presents a newly diagnosed T2D patient needing a personalised medication plan.

Label Noise SGD Provably Prefers Flat Global Minimizers