Pipeline 1 · DopaMatch

From empirical dosing to data-driven precision in Parkinson's care.

The world's first clinically viable continuous L-DOPA monitor

building the data infrastructure for precision Parkinson's therapy.

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Spun out of ShanghaiTech University · SensUs 2025 global champion team
00 / Target roadmap

Go deep in Parkinson's first, then broaden the small-molecule platform.

We start with continuous L-DOPA monitoring, then extend the same platform into kidney function, hormones, TDM, and cardiovascular small molecules.

P0 / Core disease wedge
Parkinson's
Target
L-DOPA
Stage
Animal-study prep
Timeline
2026
01 / Clinical pain chain

No monitoring -> blind dosing -> patient disability -> system drain.

The core issue in long-term Parkinson's care is not one missing product. It is a full causal chain created by the absence of continuous objective monitoring.

Core insight: once upstream monitoring breaks, downstream dosing, functional status, and care resources are all forced into reactive mode.
1
Root cause

Monitoring blind spot

There is no continuous objective monitoring of L-DOPA concentration in blood or interstitial fluid. Clinicians depend on patient recall and periodic scales.

  • No commercial device continuously monitors L-DOPA in blood or interstitial fluid
  • Clinicians rely on patient recall and periodic UPDRS, with a 2-4 week observation window
  • Clinic snapshots are affected by visit-time state and provide low-fidelity information
2
Direct consequence

Blind dose adjustment

L-DOPA remains the gold-standard therapy, but without concentration feedback, dose and timing optimization remain experience-led.

  • L-DOPA is the gold standard, yet dosing has relied on clinician experience for 60 years
  • No drug-concentration feedback means individualized dose and timing windows cannot be optimized
  • Patient self-report aligns with clinical observation only about 60% of the time
3
Clinical dilemma

Patient disability

As disease progresses, wearing-off, dyskinesia, and on-off fluctuations keep eroding daily function and quality of life.

  • About 50% of patients develop motor complications after 5 years of L-DOPA; at least 80% after 10 years
  • Aspiration pneumonia and fall-related injury are major severe outcomes in advanced disease
  • Complications become a core driver of long-term visits and payment
4
System cost

Reactive resource use

System resources are spent on complication handling instead of earlier prevention.

  • Large resources go toward motor-complication handling instead of prevention
  • Without upstream monitoring, the care value chain cannot move earlier
  • Objective monitoring can interrupt the full vicious chain
11.77M

people live with Parkinson's globally, and 80% of late-stage patients develop motor complications. L-DOPA has remained experience-dosed for 60 years; upstream objective monitoring can reshape the value chain.

01B / Nobel Archive / 2000

Arvid Carlsson

His dopamine research established the scientific foundation for L-DOPA therapy in Parkinson's disease.

Arvid Carlsson speaking at a lecture
Parkinson's today is what diabetes looked like in 2005. CGM let patients see their glucose curves for the first time and rewrote the entire disease-management paradigm. DopaMatch does the same for the most consequential drug curve in PD care.
02 / Product architecture

A technology breakthrough moves Parkinson's dosing from experience to data.

DopaMatch is not a standalone hardware idea. It combines an L-DOPA sensor, the MatchPD AI data ecosystem, and a data flywheel.

Sensor

One L-DOPA sensor

A subcutaneous single-microneedle enzymatic electrochemical sensor continuously outputs interstitial L-DOPA curves for objective drug-concentration evidence.

MatchPD AI data ecosystem

One data ecosystem entry point

Pharma real-world research：Continuous drug concentration and movement data support RWE studies. / Hospital workflow：Home-state signals become continuous curves and visit-ready reports. / Patient daily use：Symptoms, dosing, movement, and concentration changes enter one daily loop. / Academic real-world research：Structured data supports long-term PD medication and motor-complication studies.

Data flywheel

One data flywheel

Real-time drug concentration, movement sensors, and behavior logs calibrate each other to build an increasingly complete drug-motor axis.

Drug-motor axis

Objective drug-motor axis

The key difference is not measuring concentration alone. It is binding real-time drug concentration to patient motor status so clinicians can see how pharmacokinetics map to function.

02B / MatchPD AI data ecosystem

One data ecosystem entry point

The key difference is not measuring concentration alone. It is binding real-time drug concentration to patient motor status so clinicians can see how pharmacokinetics map to function.

01

Pharma real-world research

Continuous drug concentration and movement data support RWE studies.

02

Hospital workflow

Home-state signals become continuous curves and visit-ready reports.

03

Patient daily use

Symptoms, dosing, movement, and concentration changes enter one daily loop.

04

Academic real-world research

Structured data supports long-term PD medication and motor-complication studies.

03 / Closed-loop technology stack

A full-stack loop across AI, wet lab, and hardware.

The core capability is not a single model or sensor. It is an engineering loop from data, design, wet-lab validation, and hardware acquisition.

Biosensing / computational biology

  • AI-assisted directed evolution algorithms
  • Structure prediction and protein language models
  • Standardized data engineering and private datasets
  • In-house protein mutation generation algorithms
  • Dry-wet closed-loop validation system
  • Continuous L-DOPA monitoring
  • Continuous creatinine monitoring
  • GZMK binder design for ELISA
  • Odorant-binding protein design
  • GPCR Exoframe Modulator design

Hardware technology stack

  • Software-hardware co-development
  • Mixed-signal circuit design
  • Full-stack embedded-system design and validation
  • Wireless IoT technology
  • Wearable-device design validation
  • Coin-sized electrochemical front end
  • High-precision miniature electrochemical measurement platform
  • In-house integrated AFE
  • Multichannel parallel acquisition
  • AI real-time signal processing and drift compensation
  • EIS capability expansion

Future R&D pipeline

  • Cortisol
  • Homocysteine
  • Vancomycin
  • Tacrolimus
  • 5-fluorouracil
  • Atrial natriuretic peptide
04 / Platform

DopaMatch is the start. The closed-loop platform turns one biomarker into multi-target capability.

The same AI design, wet-lab validation, and miniature electrochemical hardware stack can be reused across different small-molecule targets instead of rebuilding the system target by target.

P0 · 2025–2028

L-DOPA

Continuous / PoC complete

P0 · 2025–2027

Homocysteine (Hcy)

POCT / Principle validated

P1 · 2027+

Vancomycin

Continuous TDM / Concept design

P1 · 2027+

Tacrolimus

Continuous TDM / Concept design

P2 · 2028+

Cortisol

POCT / continuous / Literature review

Target roadmap

Go deep in Parkinson's first, then broaden the small-molecule platform.

We start with continuous L-DOPA monitoring, then extend the same platform into kidney function, hormones, TDM, and cardiovascular small molecules.

Priority Target Why it matters Format Stage Timeline
P0 L-DOPA Key to Parkinson's therapy Continuous monitoring Animal-study prep 2026
P1 Creatinine Important marker for kidney-function monitoring and chronic care Continuous monitoring R&D validation 2026+
P1 Cortisol Core stress and metabolic hormone; circadian rhythm requires continuous capture POCT / continuous Pipeline design 2027+
P1 Vancomycin Core ICU anti-infective with a narrow therapeutic window requiring real-time TDM Continuous monitoring Pipeline design 2027+
P1 Tacrolimus Core anti-rejection drug for organ transplants; large interpatient variability Continuous monitoring Pipeline design 2027+
P2 Homocysteine Independent cardiovascular and cerebrovascular risk factor for high-throughput screening POCT Pipeline design 2028+
P2 5-FU / ANP Future expansion for oncology TDM and cardiovascular-state monitoring TDM / POCT Concept design 2029+
05 / Clinical value chain

Move resources from complication handling to continuous monitoring.

The value in long-term Parkinson's care comes from seeing drug concentration, motor state, and complication risk earlier instead of reacting after disability appears.

Upstream

No continuous concentration monitoring

Objective PK data is missing。L-DOPA dose adjustment still lacks continuous feedback

Midstream

Clinic-snapshot dosing

Patient recall bias。Clinicians cannot easily join pharmacokinetics, motor state, and daily events into one evidence chain

Downstream

Complication handling

Delayed long-term outcomes。Wearing-off, dyskinesia, falls, and aspiration force systems into reactive resource use

06 / Moat

Five compounding layers.

01

Twin AI engines

Engine A accelerates enzyme directed evolution; Engine B drives programmable recognition elements — new targets reuse the hardware.

02

Process know-how + IP wall

Layered microneedle modification and a growing hardware-and-enzyme patent system.

03

Clinical data flywheel

Continuous concentration × PK-PD × covariates — accuracy compounds with every new patient.

04

Multi-scenario data ecosystem

Pharma real-world research, hospital workflows, patient daily records, and academic studies share one continuous data entry point.

05

Precise positioning, no incumbent

UCSB aptamers last ~1.5h in vivo; CGM giants need 4–6 yrs to migrate stack; StrivePD has motion data, no concentration — complementary, not competitive.

From MakeSense to MatchBioTech.

The team moved from an international biosensor competition to cross-disciplinary prototype validation, clinical insight, and a focused translational direction in continuous L-DOPA monitoring.

Research · Validation and PoC

Research Edition

Focused on research validation and PoC, proving the continuous biosensor pathway first.

Clinical · Clinical continuous monitoring

Clinical Edition

Links concentration feedback, movement data, and visit reports for clinical continuous monitoring scenarios.

Medical · Medicalization and multimodal sensing

Medical Edition

Moves toward medical-device validation and multimodal sensing, preserving an expandable small-molecule monitoring platform.

Cross-disciplinary support network

WiSe Lab, Zhao Lab, iHuman, ShanghaiTech BME, and the School of Life Science support the full-stack iteration from AI-driven biomaterial design to wearable monitoring.

Team development history

  1. 2024.11 MakeSense team formed
    • ShanghaiTech was invited to participate in SensUs 2025
    • The first full-stack cross-disciplinary team was formed
    • Members came from biology, chemistry, materials, computer science, electronic information engineering, and industrial design
    • Three mentors came from biology, biomedical engineering, and design
  2. 2025.08 Champion in the Netherlands
    • Won the SensUs 2025 international championship
    • Validated the biosensor verification path
    • Beat graduate teams from Cornell, ETH Zurich, TU Delft, and others
    • Made MakeSense history and broke the 10-year record
  3. 2025.08 Commercial exploration
    • Conducted a full SensUs commercialization assessment
    • Explored commercialization for the creatinine sensor project
    • Archived patents, papers, and technical materials
    • Started engagement across education, research, industry, and commercialization fields
  4. 2025.11 Shift to L-DOPA monitoring
    • Inspired by SensUs and validated by Parkinson's clinical KOLs
    • Started clinical-translation R&D for clinical and frontier detection
    • Launched the L-DOPA monitoring pipeline
  5. 2025.11 Full R&D testing
    • Relied on WiSe Lab and Zhao Lab
    • Worked with support from iHuman, ShanghaiTech BME, and the School of Life Science
    • Advanced full-stack R&D from AI-driven biosensitive-material design to wearable monitoring
  6. 2026.03 Shanghai MatchBioTech founded
    • The team's technical innovation path was validated and in-vitro prototype tests succeeded
    • Hospital, patient, and industry research was completed
    • Collaboration with the Shanghai Clinical Research Center was established
    • The StrivePD China ecosystem outlook was established
    • Formal commercialization exploration began
  7. 2026.05 Product moves toward animal-experiment prep
    • Hardware and sensitive materials are advancing together
    • The product is about to enter animal experiments
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We are looking for first-cohort research-edition customers (CROs, pharma, academic labs) and neurology KOLs.

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