NEWOncologists studied OneRx across seven measures, a first for India. Now peer reviewed and published.·Read what they found →
The Medical AI Platform for Clinicians

Clinical evidence,
summarized in seconds.

OneRx summarises published medical evidence for doctors. Ask a clinical question. Get a cited answers in seconds, drawn from trusted medical sources and guidelines.

30,000+queries answered
2,000+clinicians
8countries
93%decision impact
OneRx app preview

Clinical Validation · PRECISION-AI

Tested in real practice, not on
synthetic data.

A prospective study across three tertiary oncology centres in India. 110 real clinical queries, five high-burden cancer types, independently rated by board-certified oncologists. Reported to SPIRIT-AI, CONSORT-AI, and APPRAISE-AI standards.

PRECISION-AI co-primary endpoints — all three reached 100% composite rates (n=110), each rejecting its null hypothesis at p<0.001

93%

Clinical decision impact

Reinforced or changed the oncologist's decision

8×

Faster to a recommendation

389s to 47s, an 87.9% reduction

+1.69

Physician confidence gain

On a 5-point scale, p<0.001

Security & Standards

Built to clinical-grade standards.

CDSCO Registered

CDSCO Registered

ORIGIN-South-DL/M/MD/034932

HIPAA compliant

HIPAA compliant

Patient data protection

DPDP compliant

DPDP compliant

Indian data protection

SOC2 Type2

SOC2 Type2

Operational security

ISO 27001

ISO 27001

Information security

ISO 13485

ISO 13485

Medical software

IEC 62304

IEC 62304

Medical software

Clinicians in leading institutions who use OneRx are

AIIMSAIIMS
Tata Memorial Cancer InstituteTata Memorial Cancer Institute
Max Healthcare HospitalMax Healthcare Hospital
Sarvodaya HospitalSarvodaya Hospital
Safdarjung HospitalSafdarjung Hospital
Sir Ganga Ram HospitalSir Ganga Ram Hospital
KIMS HospitalKIMS Hospital
Venkateshwar HospitalVenkateshwar Hospital
Yashoda HospitalYashoda Hospital
Yatharth HospitalYatharth Hospital
Baptist HospitalBaptist Hospital
MNJ Institute of OncologyMNJ Institute of Oncology
Kamla Nehru Memorial HospitalKamla Nehru Memorial Hospital
Renova HospitalsRenova Hospitals
HCGHCG
AIIMSAIIMS
Tata Memorial Cancer InstituteTata Memorial Cancer Institute
Max Healthcare HospitalMax Healthcare Hospital
Sarvodaya HospitalSarvodaya Hospital
Safdarjung HospitalSafdarjung Hospital
Sir Ganga Ram HospitalSir Ganga Ram Hospital
KIMS HospitalKIMS Hospital
Venkateshwar HospitalVenkateshwar Hospital
Yashoda HospitalYashoda Hospital
Yatharth HospitalYatharth Hospital
Baptist HospitalBaptist Hospital
MNJ Institute of OncologyMNJ Institute of Oncology
Kamla Nehru Memorial HospitalKamla Nehru Memorial Hospital
Renova HospitalsRenova Hospitals
HCGHCG

100+ hospitals where OneRx clinicians practise.

Proudly Built in India for the world.

In Active use across
8 countries.

From tertiary cancer centres in India to oncology practices across the Middle East, Central Asia, and Africa.

2,000+

clinicians

30,000+

queries answered

India flagIndia
Nepal flagNepal
Bahrain flagBahrain
Oman flagOman
Russia flagRussia
Kazakhstan flagKazakhstan
Uzbekistan flagUzbekistan
Chad flagChad

The Problem

More evidence than any doctor
can read.

And it grows every year. Two problems follow.

For Clinicians

No one can keep up.

1

The volume is impossible.

Three to four million papers a year. Ten thousand in oncology alone.

2

Guidelines move faster than memory.

Medical Guidelines and regulatory approvals update through the year. The next edition lands before the last is absorbed.

3

Decisions lean on recent reading.

Not on the full evidence. A system problem, not a clinician one.

For Hospitals

Ten doctors, ten standards.

1

Care varies by clinician.

Different sources and habits produce different conclusions for similar cases.

2

Evidence trails are scattered.

Across charts, notes, and memory. Hard to audit. Hard to defend.

3

Knowledge doesn't transfer.

Juniors inherit habits, not a shared, current evidence base.

Introducing OneRx

Medical AI platform for
evidence summary.

OneRx reads the literature, summarises what matters, and shows every source. The doctor decides. OneRx makes sure the right evidence is there when they do: current, cited, and matched to the patient.

onerx.ai
mm confirmed further treatment and evaluation
FFW29+ Activity›FFW22+ sources›

⚡ Multiple Myeloma: Confirmed Diagnosis — Treatment & Evaluation Framework

Summary

NCCN v5.2026 establishes quadruplet therapy as the preferred induction regimen for newly diagnosed multiple myeloma (NDMM), with daratumumab + bortezomib + lenalidomide + dexamethasone (Dara-VRd) as the Category 1 preferred regimen for transplant-eligible patients — daratumumab/hyaluronidase-fihj (DARZALEX FASPRO, FDA-approved for NDMM both ASCT-eligible and ineligible) is the SC formulation of choice. WHO Wiley For relapsed/refractory disease, the FDA approved teclistamab (Tecvayli) + daratumumab/hyaluronidase-fihj (March 2026) for patients with ≥1 prior line including a PI and IMiD; belantamab mafodotin-blmf (Blenrep) + bortezomib + dexamethasone (October 2025) for ≥2 prior lines; and linvoseltamab-gcpt (Lynozyfic) (July 2025) for ≥4 prior lines. Ncgindia NCCN A critical FDA black-box warning applies: PD-1/PD-L1 inhibitors combined with thalidomide analogues + dexamethasone are contraindicated in MM due to increased mortality in two randomized trials. NCCN PubMed India: The National Cancer Grid (NCG) coordinates myeloma care across 380+ centers; VRd (bortezomib + lenalidomide + dexamethasone) remains the most cost-effective triplet (incremental cost ₹2,20,093/QALY), and daratumumab has demonstrated consistent efficacy and acceptable safety in Indian relapsed/refractory patients, though access to quadruplet regimens and ASCT infrastructure remains variable across centers. PubMed Ncgindia

…

Cited.

Every summary links to its source paper. Nothing invented.

Current.

When medical guidelines and regulatory approvals update, OneRx reflects it within a week.

Genomics-aware.

Reads NGS and sequencing reports, and maps findings to guideline-based options.

Honest.

When the evidence is thin or conflicting, OneRx says so.

How OneRx Works

Four steps. Every summary.

And it grows every year. Two problems follow.

1

Structure

Reads research, trials, and journals into one searchable base.

2

Align

Matches evidence to the cancer stage and current guidelines, so the summary fits the case.

3

Preserve

Keeps every citation. Traceable, reviewable.

4

Verify

Stays current with the guidelines themselves, so a summary is never built on a superseded guideline.

Quality of Evidence

SystematicreviewEvidence-basedpractice guidelinesRandomizedControlled TrialsNon-RandomizedControlled TrialsCohort StudiesCross-sectional StudiesCase Series & Case ReportsBackground Information, Expert opinion & Non-EBM guidelinesMetaAnalysisCritical appraisalExperimental studiesObservational studies

Hours of searching, in seconds,
across departments.

Built for Clinicians

Tumour board prep

Cited, per question

35 min → <1 min

An unfamiliar regimen

Confirm and cite

22 min → 4 min

A guideline check, mid-consult

In the room

18 min → 90 sec

An NGS report to interpret

Mapped to NCCN / ESMO guidance

Genomics

Built for Hospitals

Live in weeks

Integrates with your HIS

Cloud or on-premises

Your data policy, your choice

Audit-ready by default

A trail for every summary

Faster onboarding

New consultants up to speed sooner

Return on Investment

See the return. Move the numbers.

Built on PRECISION-AI data. Change the inputs to match your practice.

Evidence Lookups Per Day

8/ day

Saved Per Lookup

5.7minutes

Measured in PRECISION-AI: 389s → 47s.

46 min

returned per clinical day

4.2 hrs / week

Each lookup saves 5.7 min, measured in the study (389s to 47s)
Lookups per day × 5.7 min × a 6-day week

Why OneRx

Sharper than a Search. Safer than a Chatbot.

Eight things set OneRx apart from a general chatbot or a medical search tool.

OneRx next to the tools doctors already try

Dimension
ChatGPTGeneral AI
UpToDate AIReference
OneRxMedical evidence summary
Built for
Everything
All specialties
Medical evidence summary
Citations
Can invent them
From own articles
Cited by default, traceable
Guideline currency
Training cutoff
Editorial cycle
Within a week
Hallucination risk
High
Low
Built not to invent
Reads a genomic report
Attempts, unverified
No
Interprets, maps to guidelines
Clinical validation
None
Editorial
PRECISION-AI, 100% accuracy
Second opinion for a doctor
No
No
Yes, evidence-grounded
Deployment
Cloud
Cloud
Cloud or on-premises

Events & Insights

Where we've been.

Stay up to date with the latest events, conferences, and webinars where we showcase how OneRx is transforming the landscape of clinical decision-making. Watch key moments and insights from our most recent activities.

For Clinicians

Try OneRx.

Three questions free, no sign-up. Web, iOS, and Android.

For Hospitals

Bring one evidence standard to your department.

Talk to a clinical lead, not a sales rep.

OneRx
MEDICAL AI PLATFORM

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