Predicta Biosciences Advances Multiple Myeloma Care with Liquid Biopsy Technology

Predicta Bioscience believes the answer lies in blood. With its flagship platform, GenoPredicta, the company is translating the depth of whole genome sequencing into a practical, minimally invasive diagnostic for blood cancers.

In October 2025, Predicta closed a $23.4 million Series A led by Engine Ventures, joined by Illumina Ventures, Mass General Brigham Ventures, and Dana-Farber’s Binney Street Capital. The new capital will expand the company’s CLIA-certified sequencing lab, scale its automation systems, and support commercialization of GenoPredicta.

The idea is simple but ambitious: take the precision of research-grade genomics and make it fast, affordable, and repeatable enough to replace a decades-old diagnostic standard.

The Diagnostic Gap in Multiple Myeloma

Multiple myeloma remains one of the most complex blood cancers to diagnose and monitor. Despite therapeutic breakthroughs — from bispecific antibodies to CAR-T cell therapies — the diagnostic side of the equation has lagged far behind.

The current standard still depends on bone marrow biopsies. These procedures are invasive, painful, and prone to sampling error because myeloma cells don’t spread evenly throughout the marrow. A single core sample can miss key mutations entirely.

Even when combined with fluorescence in situ hybridization (FISH) testing, reproducibility remains limited. Different labs use different probes, instruments, and thresholds, creating inconsistent results. For clinicians, that means critical treatment decisions are made with partial visibility. For patients, it means anxiety, repeat biopsies, and uncertainty.

Behind this stagnation is a technology problem. Bone marrow analysis relies on manual workflows and low-throughput instrumentation — from centrifuges and cytospin systems to slide scanners and manual image review. Predicta’s founders saw an opportunity to overhaul this workflow, replacing fragile manual steps with a fully automated sequencing pipeline capable of analyzing circulating tumor DNA from a simple blood draw.

A Blood-Based Alternative

Predicta’s answer is to trade bone marrow aspiration for a simple blood draw. Its flagship diagnostic, GenoPredicta, uses whole genome sequencing (WGS) to analyze tumor DNA and circulating myeloma cells from either bone marrow or peripheral blood.

In practical terms, that means swapping microscopes and glass slides for automated library prep systems, high-throughput sequencers, and cloud-based bioinformatics pipelines. The platform’s infrastructure links sample intake to data analysis without manual intervention, cutting turnaround times while improving accuracy.

Once sequenced, data flow through Predicta’s proprietary software for variant calling, structural rearrangement detection, and risk classification aligned with IMWG (International Myeloma Working Group) guidelines. The platform can:

• Identify high-risk genomic features linked to disease progression.
• Detect BCMA and GPRC5D mutations that predict therapy resistance.
• Match or exceed the accuracy of FISH while uncovering additional variants missed by traditional methods.

A version for minimal residual disease (MRD) monitoring is in development for release later in 2025. This will enable clinicians to track treatment response through serial blood tests instead of repeated bone marrow biopsies — a change that could redefine the patient experience entirely.

How the Work Gets Done

Predicta’s sequencing pipeline runs like a production line designed for discovery. Inside its CLIA-certified Cambridge facility, the company’s workflow connects every stage of testing through automated instrumentation and integrated software systems.

The process begins with sample intake automation: robotic systems handle barcoding, tracking, and aliquoting blood or bone marrow samples into standardized microplates. These are then processed by liquid-handling robots and automated nucleic acid extraction systems, reducing the variability and contamination risk common in manual prep.

From there, library construction—a historically slow and error-prone step—is executed through programmable liquid handlers linked to NGS platforms like Illumina’s NovaSeq and NextSeq systems. Once sequencing is complete, data are routed automatically into a cloud-based bioinformatics pipeline that performs alignment, variant calling, and interpretation using validated algorithms.

Throughout, built-in QC checkpoints monitor sequencing depth, coverage, and base quality in real time. Reports are generated through a secure interface that integrates directly with electronic medical records and oncology decision-support tools, eliminating redundant transcription and manual report compilation.

Even equipment management is automated: Predicta uses IoT-enabled lab instruments with self-calibration logs and predictive maintenance scheduling, ensuring uptime without constant technician intervention.

In the end, what Predicta is building is more than a test—it’s a reproducible, semi-autonomous diagnostic factory. A place where each sample moves seamlessly from patient to insight, powered by the quiet hum of sequencing machines and the code that makes them work together.

Competitive Position and Validation

Predicta’s advantage isn’t just that it replaces a biopsy with a blood draw—it’s that its entire workflow is reproducible, scalable, and digital.

The GenoPredicta platform has already seen research use at Dana-Farber, where investigators apply it to risk stratification and therapy selection, especially for patients receiving BCMA-targeting therapies. Unlike conventional FISH or PCR assays that process samples one at a time, GenoPredicta’s pipeline can batch, sequence, and analyze dozens simultaneously with minimal technician oversight.

Each run feeds into an integrated data layer combining genomic sequencing, cell-free DNA analytics, and machine learning–based variant interpretation. That infrastructure allows for automated cross-checking against large reference datasets, improving both sensitivity and specificity.

For clinicians, the difference shows up in turnaround time and confidence. Reports that once took weeks and required multiple labs can now be generated within days, complete with genomic annotations, variant significance summaries, and therapeutic relevance notes.

For patients, it means fewer invasive procedures. For researchers, it means higher data quality. And for hospitals, it offers a digital-first diagnostic workflow that can plug directly into LIS and EHR systems already in use.

Leadership Tied to Genomics and the Clinic

Predicta’s leadership combines deep experience in genomics, clinical oncology, and diagnostic commercialization—a rare mix that helps bridge discovery science and the realities of clinical adoption.

Brian McKernan, appointed CEO in 2025, is a three-time biotech founder whose companies helped shape the early human genome sequencing era. At Fluent BioSciences, later acquired by Illumina, he led teams that automated single-cell sequencing workflows, replacing dozens of manual steps with fully integrated microfluidic systems. That experience now informs Predicta’s approach to automating every stage of diagnostic testing—from sample prep to variant interpretation.

The company’s scientific co-founders—Drs. Irene Ghobrial, Kenneth Anderson, Gaddy Getz, and Romanos Sklavenitis-Pistofidis—bring decades of experience treating and studying multiple myeloma. They’ve built Predicta’s development process around clinical realities: turnaround times, data interpretation, and integration into oncologists’ existing diagnostic workflows.

Much of the work happens within Predicta’s CLIA-certified sequencing lab in Cambridge, designed for both discovery and clinical use. The lab houses liquid handlers, automated pipetting robots, and next-generation sequencing (NGS) instruments capable of running hundreds of samples in parallel. Downstream, the company’s data analysis cluster integrates quality control metrics, variant classification algorithms, and report generation pipelines—all tuned to maintain reproducibility across runs.

It’s genomics as an engineered system rather than a series of experiments.

Looking Forward

Predicta Biosciences is entering a crowded but fast-moving space: the convergence of genomics, automation, and oncology diagnostics. Its challenge isn’t proving that sequencing works—it’s proving that sequencing can work at scale, in real-world labs, for real clinicians.

The company’s Series A gives it the resources to expand its sequencing operations, strengthen regulatory footing, and push its pipeline of blood-based assays beyond multiple myeloma. ImmunoPredicta, a forthcoming platform for profiling immune responses in myeloma patients, is next in line, with long-term plans to extend into autoimmune diseases and other hematologic malignancies.

But the real story here is process, not product. Predicta’s work represents how diagnostics are evolving—from craft to system, from bench science to software-driven precision. If GenoPredicta can consistently replicate its research-grade accuracy in everyday clinical use, it could redefine how oncologists gather and act on genomic data.

The shift would mean fewer procedures, faster answers, and a deeper understanding of how therapies interact with a patient’s own molecular landscape.