> ## Documentation Index
> Fetch the complete documentation index at: https://docs.revilico.bio/llms.txt
> Use this file to discover all available pages before exploring further.
# Beginning Your First End-to-End Campaign
> A step-by-step guide to standing up your first full computational + experimental drug discovery campaign with Revilico — from therapeutic strategy through parallel execution.
## Overview
Your first campaign with Revilico is a joint effort: our team works alongside you to lock in strategy, mine prior knowledge, and scope assays in parallel with the computational build-out, so that by the time compounds are ready for down-selection, everything downstream — CRO quotes, protein production, assay validation — is already lined up. This guide walks through the six steps we take together to get a campaign fully situated, from first conversation to parallel execution.
| Step | Name | Owner |
| ---- | ----------------------------------------------- | --------------------------- |
| 1 | Therapeutic Strategy & Positioning | Joint |
| 2 | Prior Knowledge Calibration | Revilico |
| 3 | Assay Strategy (First-Line & Early Second-Line) | Joint, in parallel with CRO |
| 4 | Computational Campaign Design | Revilico |
| 5 | Project Setup & Centralization | Revilico |
| 6 | Parallel Execution | Joint |
Steps 3 and 4 run **in parallel**, not sequentially. The goal is that the only thing standing between strategy and a confirmed lead set is a single med-chem down-selection step at the end.
***
## Step 1 — Finalize Therapeutic Strategy & Positioning
Before any computational or experimental work begins, we align on the shape of the campaign itself.
* **Therapeutic strategy** — the disease area, mechanism of action, and modulation approach (inhibition, activation, allosteric modulation, PPI disruption, etc.) you intend to pursue.
* **Market positioning** — where this program sits relative to existing and pipeline therapies, and what differentiates it.
* **Potential ROI** — a working estimate of commercial opportunity that justifies the scope of computational and experimental investment.
* **Pocket of interest** — the specific binding site, domain, or interface you want to drug, and why it's tractable.
This step produces the therapeutic hypothesis that every subsequent step is built around.
***
## Step 2 — Identify All Prior Knowledge
Before designing a single assay or docking run, we mine everything already known about your target so the campaign is calibrated against real biology and chemistry from day one — the same process we ran for your TNFα program, including the full prior compound set pull.
All available co-crystal structures for your target, including the bound ligand identity and resolution. These define validated binding poses and active-site conformations.
Residues known from structural or mutagenesis data to be mechanistically critical — contact residues from co-crystals, alanine-scan hot spots, or literature-annotated catalytic residues.
Compounds with documented activity against your target — pulled from ChEMBL, PubChem BioAssay, patents, and the literature.
For each known binder: the reported activity value (IC₅₀, Kᵢ, Kd, EC₅₀) and exactly how it was measured — assay format, biochemical vs. cellular, and conditions.
This prior-knowledge set becomes the calibration foundation referenced throughout Steps 3 and 4 — it's what lets us benchmark both computational engines and assay formats against ground truth before committing to production scale.
***
## Step 3 — Identify First-Line & Early Second-Line Assays
This is the first thing that needs to be locked down, and it runs **in parallel with the computational build-out** in Step 4 — so that the only remaining decision downstream is a med-chem-reviewed down-selection of compounds.
We finalize the assay strategy together with your CRO. For each assay under consideration, we work through:
What are we actually trying to measure — binding affinity, functional inhibition/activation, cellular potency, selectivity? Define the readout before choosing the format.
What reagents does the assay require, and are they already available, or do they need to be sourced or synthesized?
Which protein constructs need to be expressed? From-scratch expression or off-the-shelf/commercial protein — and if from scratch, what expression system and timeline?
What tags are required for the assay format (e.g. C-terminal 6×His for SPR), and which protein variants are needed (wild-type plus any relevant mutants)?
Single-dose screening for rapid triage, or full dose-response for confirmed hits? This determines throughput and cost per assay round.
Is there a validated kit or off-the-shelf assay we can use directly, or does the assay need to be set up and validated internally before it can run at scale?
Running this step in parallel with computational design (Step 4) means CRO lead times, protein expression, and assay validation are already progressing while the compound funnel is being built — so nothing sits idle waiting on the other.
***
## Step 4 — Define the Computational Campaign
We help finalize the computational strategy with you, including:
* **Docking configuration** — docking box definition and coordinates, and the exhaustiveness setting for each docking stage.
* **Generative engines** — which generative chemistry engines are needed to expand or design around your initial chemical matter.
* **MD analyses** — which molecular dynamics analyses are required (protein-in-water conformational sampling, protein-ligand stability, membrane permeability, etc.).
* **FEP** — whether free energy perturbation is warranted for this program, and at what stage (typically post hit-to-lead, on a narrowed set).
Alongside the strategy itself, we provide recommended next steps and forward you video tutorials and written guides so your team can execute directly in the Revilico platform as the campaign progresses.
***
## Step 5 — Set Up Your Project
Once Steps 1–4 are scoped, we create a dedicated **Revilico OS Project** for the target. This project becomes the single place where everything lives:
* The full computational campaign — docking runs, MD, FEP, generative design
* The full experimental campaign — assay results, CRO deliverables
* The therapeutic strategy and plan documented in Steps 1–2
* All CRO quotes, which we can help design on your behalf
Centralizing the campaign here means every stakeholder — computational, experimental, and CRO-facing — is working from the same source of truth as the program progresses.
***
## Step 6 — Move Into Parallel Execution
With strategy locked, prior knowledge mined, assays scoped, computational design finalized, and the project centralized, we move into execution — computational and experimental workstreams running **simultaneously** rather than sequentially.
Because the assay strategy (Step 3) and computational design (Step 4) were finalized in parallel rather than in sequence, this next iteration moves significantly faster than a first-time campaign: the only gate between the computational funnel and wet-lab confirmation is a single medicinal chemistry review and down-selection of the recommended compound set.
***
## Quick Reference Checklist
**Step 1 — Therapeutic Strategy**
* Define therapeutic strategy, mechanism, and modulation approach
* Establish market positioning and potential ROI
* Identify the pocket of interest
**Step 2 — Prior Knowledge**
* Pull all available co-crystal structures
* Identify key / hot-spot residues
* Compile known binders with activity values and assay provenance
**Step 3 — Assay Strategy (parallel with Step 4)**
* Define key measurements per assay
* Confirm required reagents and protein constructs
* Decide from-scratch expression vs. off-the-shelf protein
* Confirm tags and variants needed
* Decide single-dose vs. dose-response format
* Confirm whether assay validation is needed or a kit is available
* Finalize with CRO
**Step 4 — Computational Campaign**
* Define docking boxes, coordinates, and exhaustiveness
* Identify generative engines needed
* Scope required MD analyses
* Determine if/when FEP is warranted
**Step 5 — Project Setup**
* Create dedicated Revilico OS Project for the target
* Centralize computational + experimental plans, strategy, and CRO quotes
**Step 6 — Execution**
* Launch computational and experimental workstreams in parallel
* Reserve med-chem review and down-selection as the final gating step