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Sequel Med Tech

Sequel Med Tech

Manchester, United States· Est.
sequelmedtech.com
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Private Company

Total funding raised: $20M

Overview

Sequel Med Tech is a private, commercial-stage medical device company pioneering a novel automated insulin delivery (AID) system called twiist. The system differentiates itself through direct volume measurement of insulin, pharmacy channel distribution for affordability, and utilization of the Tidepool algorithm. Co-founded by renowned inventor Dean Kamen and other healthcare veterans, Sequel aims to address the significant unmet need in the diabetes market, where a majority of insulin-requiring patients are not yet using AID technology.

DiabetesEndocrinology

Technology Platform

The twiist Automated Insulin Delivery (AID) system, featuring direct volumetric measurement of insulin microdoses, integrated with the Tidepool algorithm for hybrid closed-loop control, and designed for pharmacy channel distribution.

Funding History

2
Total raised:$20M
Series A$15M
Seed$5M

Opportunities

The primary opportunity is addressing the ~63% of insulin-requiring patients not using AID systems by offering a more affordable, pharmacy-accessible product.
Secondary opportunities include expanding into type 2 diabetes management and leveraging its precise delivery platform for partnerships with pharmaceutical companies on other injectable therapies.

Risk Factors

Key risks include commercial execution challenges in establishing pharmacy reimbursement, intense competition from entrenched AID market leaders, and the technological and operational risks associated with launching a novel medical device.
Financial reliance on private funding until profitability is achieved also presents a risk.

Competitive Landscape

Sequel competes in the automated insulin delivery market against large, established players like Medtronic (MiniMed 780G), Insulet (Omnipod 5), and Tandem Diabetes Care (t:slim X2 with Control-IQ). Its differentiation is based on direct insulin volume measurement, a targeted pharmacy distribution model for cost savings, and the use of the Tidepool algorithm.

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