Results for “meddpicc”

Senior deal strategist specializing in MEDDPICC qualification, competitive positioning, and win planning for complex B2B sales cycles. Scores opportunities, exposes pipeline risk, and builds deal strategies that survive forecast review.

Plan and execute enterprise sales cycles using MEDDICC qualification, mutual action plans, and stakeholder mapping to systematically close complex deals.

Ad-Hoc Raw Upload to Databricks

Loads Therapeutics Data Commons (TDC, PyTDC) AI-ready drug-discovery datasets and benchmarks — ADME, toxicity, drug-target interaction (DTI), scaffold splits, and molecular oracles for therapeutic ML and pharmacological prediction. Use when fetching a standardized benchmark dataset, applying scaffold or cold-split evaluation, or sourcing labeled molecules for ADMET, toxicity, or DTI modeling. Sources data, splits, and oracles only — defer molecular featurization (ECFP/fingerprints), model training, and transformers to a molecular-ML skill (e.g. deepchem). Part of the AlterLab Academic Skills suite.

Filters and prioritizes compound libraries in drug discovery using drug-likeness rules, structural alerts, complexity metrics, and a query language.

This skill recommends monitoring desmopressin (DDAVP) doses and adjusting them as needed in patients who have recently started antiepileptic drugs (AEDs). It is triggered when a patient initiates AED therapy and requires DDAVP management for diabetes insipidus.

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.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Access AI-ready drug discovery datasets and benchmarks from Therapeutics Data Commons, covering ADME, toxicity, drug-target interactions, and molecular generation with standardized splits and evaluation metrics.

Configure Cedar policy enforcement and Ed25519 signed receipts for Claude Code tool calls. Use when setting up projects that need cryptographic audit trails, policy-gated tool execution, or compliance-ready evidence of agent actions.

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.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Use DuDuClaw — a self-hosted AI-employee platform — for cross-session memory, team-shared wiki knowledge, task boards, and messaging humans over LINE/Telegram/Discord/Slack. Applies when the user mentions DuDuClaw, asks their agent to remember things durably, or wants to reach people on messaging channels from an agent.

Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.

Filtros de química medicinal. Aplique regras de similaridade a fármacos (Lipinski, Veber), filtros PAINS, alertas estruturais, métricas de complexidade, para priorização de compostos e filtragem de bibliotecas.

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.

Interact with Paddock — AI agent orchestration dashboard. Use when registering agents, managing tasks, syncing skills, or querying agent/task status via Paddock APIs.

Streams MySQL or MariaDB row-level changes into Redpanda or Kafka via the mysql_cdc input, covering binlog setup, snapshots, checkpointing, per-table routing, AWS RDS IAM auth, and Enterprise lakehouse destinations.

Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.

Use for PPC work when Codex should validate Meta catalog, feed, event, availability, and dynamic product ad readiness.

Simulates meiotic recombination to produce offspring genomes from parent pairs, modeling Mendelian segregation, de novo mutation, sex determination, trait inference, and clinical evaluation against a disease registry.

Monitors and manages Dell PowerEdge servers via the iDRAC Redfish API, covering hardware status, health, sensors, power operations, inventory, and event logs.

Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.

Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.

Perform cheminformatics tasks including molecular I/O, descriptor calculation, fingerprinting, substructure search, and similarity analysis using the RDKit library.

Ad intelligence and app analytics assistant for searching ad creatives, analyzing apps, rankings, downloads, revenue, and market insights. Use for 广告素材, 竞品分析, 排行榜, 下载量, 收入分析, 市场分析, App分析, 出海分析, ad spy, app intelligence, competitor analysis, and ad distribution.

>- DMAIC (Define-Measure-Analyze-Improve-Control) — Six Sigma structured problem-solving for chronic, data-driven quality improvement projects. Use when a problem recurs despite corrective actions, when a process needs systematic capability improvement, or when a customer requests a Six Sigma approach. Use 8D for reactive single-incident problems; use DMAIC for recurring systemic issues requiring statistical analysis. Covers IATF 16949 §10.1 and ISO 9001 §10.3.

Monitor and manage Dell PowerEdge servers via the iDRAC Redfish API for iDRAC 8 and 9.

Predict 3D binding poses of small molecule ligands to protein targets using diffusion-based molecular docking, supporting single complexes, batch processing, and virtual screening.

Access AI-ready drug discovery datasets, benchmarks, and molecular oracles from Therapeutics Data Commons for therapeutic machine learning and pharmacological prediction.

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.

Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.

Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.

Use the DuDuClaw MCP tools (persistent memory, shared wiki, task board, channel messaging) when the user asks to remember something across sessions, share knowledge with their team's AI employees, manage tasks, or message someone on LINE/Telegram/Discord/Slack. Requires a running DuDuClaw gateway (`npx duduclaw onboard` to set up).

Deploys and configures CrowdStrike Falcon EDR sensors across Windows, macOS, and Linux endpoints, sets prevention and response policies, validates deployment, and integrates with SIEM platforms.