Initial Release help-frontend

Dr. Frontend

Report View

A flexible, JSON-driven report layout with a floating left nav, collapsible sections, superscript citation links, and a bibliography. Inspired by theTarget Nexus RunReportView.

How it works

The report is driven entirely by a ReportData JSON object. The server (or an AI agent) returns this JSON, and the component renders it — no hardcoded sections. As new data arrives (new evidence, new risks, new citations), the lists grow and the report updates.

Sections are data, not code

Each section in the sections[] array has atype that determines how it renders:

TypeRenders asGrows over time?
summaryProse paragraph with inline citation linksContent is replaced
listBullet list with variant styling (strengths, risks, gaps, steps)Yes — items are appended
metricsGrid of key-value cards with directional indicatorsMetrics are updated
tableData table with headers and rowsYes — rows are appended
textMulti-paragraph text with citation supportContent is replaced

Floating left nav

A sticky sidebar on the left tracks which section is in view usingIntersectionObserver. Clicking a nav item smooth-scrolls to that section. The nav is auto-generated from the sections[] array — add a section to the JSON and it appears in the nav.

On mobile (lg: breakpoint), the nav is hidden and sections stack vertically.

Collapsible sections

Any section can be made collapsible by settingcollapsible: true in the JSON. Set defaultCollapsed: true to start collapsed. This is useful for detailed sections (safety data, resistance mechanisms) that most readers skip on first pass.

{
  id: "safety-assessment",
  title: "Safety Assessment",
  type: "text",
  collapsible: true,
  defaultCollapsed: true,
  content: "Preclinical safety evaluation..."
}

Superscript citation links

Text containing [1] or[2,3] markers is parsed into superscript links. The pattern works in two ways:

  1. Inline markers — write [1] directly in the text string. The parser extracts them and creates superscript links.
  2. Citations array — add citation keys to thecitations field of a list item. They are appended to the text automatically.

Hover a superscript to see the full citation in a tooltip. Click it to smooth-scroll to the bibliography entry, which highlights briefly with a blue background.

// Inline marker in text
{ text: "KRAS G12C is present in ~13% of NSCLC [1]" }

// Citations array (appended automatically)
{ text: "Strong GWAS signal across ancestries", citations: ["1", "6"] }

// Both produce superscript links that:
//   hover → tooltip with title, authors, year, DOI
//   click → smooth-scroll to bibliography entry

Usage

import { ReportView } from
  './report-view/ReportView';

<ReportView data={reportJson} />

ReportData shape

interface ReportData {
  id: string;
  title: string;
  subtitle?: string;
  timestamp: string;
  status: "draft"|"review"|"final";
  metadata: Record<string, string>;
  sections: ReportSection[];
  bibliography: BibliographyEntry[];
}

Section types

  • summary — prose with citations
  • list — cited items (strengths, risks, gaps, steps)
  • metrics — KPI cards
  • table — data table
  • text — multi-paragraph

List variants

  • strengths — green check icon
  • risks — red warning icon
  • gaps — amber question icon
  • steps — blue chevron icon
  • neutral — gray list icon

Key features

  • • Floating sticky left nav
  • • Scroll-spy highlights active section
  • • Collapsible sections (accordion)
  • • Superscript citation tooltips
  • • Click citation → scroll to bib entry
  • • JSON-driven — no hardcoded sections
  • • Lists grow as data arrives
  • • Status badge (draft/review/final)
  • • Metadata pills from key-value pairs

Origin

Based on the RunReportView component fromTarget Nexus, generalized into a reusable pattern for any JSON-driven report.

Live Demo

A target druggability assessment report with 9 sections, 8 bibliography entries, and collapsible detail sections. Try hovering and clicking the superscript citation numbers.

Target Druggability Assessment: KRAS G12C

Comprehensive evaluation of KRAS G12C as a therapeutic target in non-small cell lung cancer

Review
Therapeutic Area: OncologyIndication: NSCLCTarget: KRAS G12CModality: Small MoleculeStage: Lead Optimization

Generated May 28, 2026 at 02:30 PM

Executive Summary

KRAS G12C represents a validated oncology target with strong genetic evidence linking activating mutations to tumor progression in NSCLC [1]. Covalent inhibitors have demonstrated clinical proof-of-concept, with sotorasib and adagrasib achieving regulatory approval [2][3]. However, acquired resistance mechanisms — particularly through bypass signaling via SHP2 and SOS1 — remain a significant challenge [4]. Our internal compound series shows promising selectivity (>100x vs wild-type KRAS) and favorable pharmacokinetic properties in preclinical models [5]. The recommendation is to advance to IND-enabling studies with parallel investment in combination strategies to address resistance.

Key Metrics

Overall Confidence

High (0.85)

Genetic Evidence

Strong

Druggability Score

8.2 / 10

Safety Risk

Moderate

Competitive Intensity

High

IP Freedom

Favorable

Key Strengths

  • KRAS G12C mutation is present in ~13% of NSCLC patients, representing a well-defined patient population with established companion diagnostics [1]
  • Covalent binding mechanism provides high selectivity for the mutant form over wild-type KRAS, reducing off-target toxicity concerns [2]
  • Clinical validation through approved therapies (sotorasib, adagrasib) de-risks the target biology [3]
  • Internal compound RCH-4471 demonstrates Kd < 5nM with >200x selectivity vs WT-KRAS in biochemical assays [5]
  • Strong GWAS signal across multiple ancestries supports causal role in tumorigenesis [1][6]

5 items

Key Risks

  • Acquired resistance develops in most patients within 6-12 months, primarily through KRAS amplification, secondary mutations (Y96D), and bypass pathway activation [4]
  • Competitive landscape is crowded with multiple next-generation inhibitors in Phase II/III trials [7]
  • Brain penetration of current compound series is suboptimal (Kp,uu brain = 0.15), limiting efficacy against CNS metastases [5]

3 items

Knowledge Gaps

  • Optimal combination partners for overcoming resistance remain undefined — SHP2 and SOS1 inhibitors show promise but lack clinical validation in combination [4]
  • Long-term safety profile of covalent KRAS inhibitors beyond 24 months is not yet characterized [3]
  • Biomarker strategy for identifying patients most likely to benefit from combination therapy needs development
  • Impact of tumor heterogeneity on treatment response is poorly understood in the KRAS G12C context

4 items

Recommended Next Steps

  • Complete 28-day GLP toxicology studies in two species (target Q3 2026)
  • Initiate combination screening with SHP2 inhibitor (RCH-8832) in PDX models
  • Develop CNS-penetrant backup series with target Kp,uu > 0.5
  • File IND application targeting Q1 2027 for first-in-human dose escalation
  • Engage regulatory affairs for companion diagnostic strategy alignment

5 items

Bibliography

1

KRAS G12C mutation frequency in non-small cell lung cancer: a systematic review and meta-analysis

Chen H, Zhang J, Wang L, et al. (2024). Journal of Thoracic Oncology

doi:10.1016/j.jtho.2024.01.015
2

Covalent targeting of KRAS G12C: from chemical biology to clinical translation

Ostrem JM, Shokat KM (2023). Nature Reviews Drug Discovery

doi:10.1038/s41573-023-00784-x
3

Sotorasib versus docetaxel for previously treated KRAS G12C-mutated NSCLC: CodeBreaK 200 final analysis

de Langen AJ, Johnson ML, Mazieres J, et al. (2024). New England Journal of Medicine

doi:10.1056/NEJMoa2404613
4

Mechanisms of acquired resistance to KRAS G12C inhibition in cancer

Awad MM, Liu S, Rybkin II, et al. (2024). Nature Medicine

doi:10.1038/s41591-024-02891-5
5

RCH-4471: a next-generation covalent KRAS G12C inhibitor with enhanced selectivity and pharmacokinetic properties

Internal Report — Roche Discovery Chemistry (2026). Internal Technical Report RCH-TR-2026-0089

6

Cross-ancestry genome-wide association study of lung adenocarcinoma identifies novel susceptibility loci

McKay JD, Hung RJ, Han Y, et al. (2023). Nature Genetics

doi:10.1038/s41588-023-01525-x
7

Competitive landscape of KRAS G12C inhibitors: next-generation approaches and combination strategies

Hallin J, Engstrom LD, Hargis L, et al. (2025). Cancer Discovery

doi:10.1158/2159-8290.CD-25-0142
8

Single-cell transcriptomic profiling of KRAS G12C-mutant NSCLC reveals variant-specific immune microenvironment features

Xue JY, Zhao Y, Aronowitz J, et al. (2025). Cell

doi:10.1016/j.cell.2025.02.018

Report ID: RPT-2026-0042

Generated May 28, 2026