About Charrette Advisory

Before we commence any project, we learn the technology the underlying science and where it’s soft; the design and appropriateness of the data; the competitive and IP landscape; the clinical use cases and workflow; the on-market pricing and throughput it will need to be viable; and the contracts, publications, and relationships required for standup. Articulating value at this level is not an “effective storytelling” exercise, but the deliberate construction of the evidence, relationships, and institutional momentum needed to change practice.

Our Purpose

Today in MedTech and biopharma, the largest barrier is substantiating a product’s necessity and reasonable fit to the institutions that gatekeep and govern access to the market.

These include AMA bodies that shape use case and coding architecture, CMS and commercial payers that craft coverage and reimbursement policies, HTA bodies that recommend evaluation models, guideline organizations that shape standards of care, and health system Value Analysis or Formulary Committees that determine whether a product is purchased.

Across this ecosystem, we build the evidence, strategic infrastructure, and stakeholder relationships needed to shepherd a technology from early validation through standard of care. That is our purpose. That is what we do.

Industry Sectors Served

Molecular Diagnostics

We work across PCR, NGS, and other platforms, but the value question is set by intended use (e.g. screening, diagnosis, aid-in-diagnosis, prognosis, therapy selection, monitoring), care setting, and patient population, since each requires a different evidence strategy. Whether a test reaches the clinic as a laboratory developed test (LDT) under CLIA or a distributed FDA-cleared kit affects the path, but our work is the typically more fundamental evidence and case strategy.

Core Competencies

  • Oncology: comprehensive genomic profiling, companion diagnostics, liquid biopsy (ctDNA), molecular residual disease (MRD), multi-cancer early detection (MCED), and hereditary cancer risk.
  • Infectious disease: syndromic panels, sexual health and STI, antimicrobial resistance, sepsis and bloodstream infection, and viral load monitoring.
  • Reproductive and prenatal: noninvasive prenatal testing (NIPT), expanded carrier screening, and preimplantation genetic testing (PGT).
  • Inherited and rare disease: germline panels, newborn screening, and exome or genome sequencing for undiagnosed disease.
  • Pharmacogenomics: drug metabolism and response.
  • Transplant: donor-derived cfDNA for rejection surveillance, and HLA typing.

Digital Health and AI/ML

We work across model classes, from classical ML through deep learning to foundation models and large language models. Whether a model is locked or continuously learning changes how its performance has to be evidenced over time. Clearing FDA and revenue generation are different problems, and coverage is almost always the most difficult part. Many digital products fall outside any existing benefit category, so building a payment pathway or adoption strategy where none are defined becomes as much of the job as generating the evidence.

Core Competencies

  • AI/ML embedded in devices and diagnostics (SiMD): algorithms that read radiology, pathology, ophthalmology, ECG, and EEG, and models built into instruments and devices (the regulatory unit).
  • Wearables and apps: connected sensors and consumer devices for continuous physiologic and behavioral capture, including remote patient monitoring (RPM).
  • Digital diagnostics: tests that reach a diagnostic, screening, or monitoring result from digital signals such as voice, ocular, and facial measures, skin images, or wearable-derived physiology, rather than a biochemical assay.
  • Standalone Software as a Medical Device (SaMD): standalone software that performs a medical function in its own right.
  • Digital therapeutics (DTx): a growing sector, with software delivering a strictly digital clinical intervention

Biopharma

We begin with the molecular architecture of disease: its epidemiology and etiology, underlying biological pathways, and the predictive or prognostic relevance of its biomarkers. This understanding shapes target-population definition, patient identification, trial design, and the clinical use of large-molecule biologics and advanced therapies, which often require complex delivery pathways and deep health-system partnerships for evidence generation, administration, and longitudinal follow-up. Where companion or complementary diagnostics are required, they must advance as part of an integrated therapeutic, evidence, access, and care-delivery strategy rather than as a separate program.

From there, modality shapes launch complexity. Small-molecule commercialization follows a relatively established playbook, whereas advanced therapies do not. Evidence may rely on single-arm trials, surrogate endpoints, and accelerated approval, leaving uptake and premium pricing contingent on confirmatory studies and long-term durability data. Delivery adds another layer, particularly for autologous cell therapies: limited certified centers, apheresis, weeks of manufacturing, and six-figure acquisition costs carried by hospitals until reimbursement under buy-and-bill. For six- and seven-figure, single-administration therapies, access may also require outcomes-based contracts, warranties, risk-sharing agreements, or multiyear payment models.

Core Competencies

  • Cell and gene therapies (CGT): CAR-T, TCR-T, TIL, and NK-cell; AAV and lentiviral gene therapy, in vivo and ex vivo; CRISPR/Cas, base, and prime editing.
  • Antibody and RNA therapeutics: antibody-drug conjugates (ADCs) and bispecifics; siRNA and antisense oligonucleotides (ASOs).

Proven Impact Across Business Stages

If you’re ready to bring clarity to your strategy and move forward with confidence, Charrette Advisory is here to support you.

(914) 953-4051