Sapient Launches DynamiQ™ as Its Next-Generation Data Insights Engine for Drug Discovery and Development
Sapient, a leader in multi-omics data generation for biomarker discovery and clinical insight delivery, has launched the next generation of its multi-omics and real-world data (RWD) human biology database, now branded as the DynamiQ™ Insights Engine, which increases the speed, versatility, and depth of analyses that Sapient can perform to inform drug discovery and precision drug development strategies.
DynamiQ features an expanded data lakehouse infrastructure, developed in collaboration with Sapient's partner Rancho Biosciences, that enables rapid curation of Sapient's unique datasets comprising thousands of protein, metabolite, lipid, and cytokine measures per sample alongside matched genomic and RWD including electronic health records (EHR), lab measures, and clinical outcomes. This data has been collected and integrated for more than 56,000 samples from diverse individuals across multiple timepoints, making DynamiQ among the most deeply phenotyped datasets available for longitudinal analysis.
Data has been harmonized across conditions, diagnoses, and outcomes, allowing for rapid creation of cohorts in which to discover, validate, and characterize biomarkers or therapeutic targets. It also provides longitudinal views of patient journeys to identify dynamic drivers of disease and drug response and to compare disease progression and treatment-response patterns across individuals and over time.
'Disease processes aren't static, and that's why DynamiQ is our differentiator,' said Dr. Jonathan Usuka, Chief Executive Officer at Sapient. 'We're focused on the deep characterization of dynamic molecular processes which are read out by proteins and metabolites that modulate, or are modulated by, disease and exposures. We have these multi-omic measures from samples collected in the same patients at different timepoints, and when we combine those with inputs from their clinical data, we can better decipher multifactorial diseases in the context of the patient's real-world experience – how disease subtypes manifest, how lifestyle factors contribute, and how drug exposure and drug adherence impact biological mechanisms and clinical outcomes. This becomes extremely powerful to understand how a therapy will actually work in a patient, to better predict response and stratify patients that are most likely to benefit from a given therapy.'
'With DynamiQ's next-generation functionality and harmonized datasets, we increase the depth and breadth of analyses we can perform for biomarker discovery, target identification, and clinical insight delivery,' said Dr. Tao Long, Co-Founder and Head of Data Science at Sapient. 'We can readily analyze molecular interactions across omics layers, rapidly build cohorts from standardized patient data, and validate discoveries from client studies in these independent populations. Importantly, because our multi-omics datasets are nontargeted they are ideal for AI and machine learning-based analysis to uncover new subgroups, novel biomarkers, and targets.'
Sapient will offer guided analyses using the DynamiQ Insight Engine as part of clients' multi-omic studies or for standalone biocomputational projects aimed at elucidating novel biomarkers, drug targets, and diagnostics.
About Sapient
Sapient is a leader in multi-omics data generation and insight delivery, providing bespoke services for proteomics, metabolomics, and lipidomics that enable biopharma sponsors to go beyond the genome to accelerate precision drug development.
Utilizing cutting-edge, high-throughput mass spectrometry and biocomputational frameworks, Sapient enables comprehensive biomarker-phenotype mapping across thousands of biosamples for discovery of robust protein, metabolite, and lipid biomarkers, drug targets, and clinical signatures of drug response. The company's DynamiQ™ Insights Engine — a longitudinal database of integrated multi-omics and real-world data collected from tens of thousands of samples — enables rapid drug target identification, biomarker discovery and validation, and translational insights across all stages of drug development. For more information, visit sapient.bio.
View source version on businesswire.com:https://www.businesswire.com/news/home/20250430976417/en/
CONTACT: Media Contact:
Carla Nieser
Head of Marketing, Sapient
[email protected]
858.290.7010
KEYWORD: UNITED STATES NORTH AMERICA CALIFORNIA
INDUSTRY KEYWORD: DATA MANAGEMENT HEALTH TECHNOLOGY HEALTH TECHNOLOGY PHARMACEUTICAL BIOTECHNOLOGY
SOURCE: Sapient
Copyright Business Wire 2025.
PUB: 04/30/2025 07:14 AM/DISC: 04/30/2025 07:13 AM
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Condensed Consolidated Statements of Operations and Comprehensive Loss (In thousands, except per share amounts) (Unaudited) Three-Month Periods Ended Six-Month Periods Ended June 30, June 30, 2025 2024 2025 2024 Revenues: Product revenues $ — $ — $ — $ — Total revenues — — — — Cost and expenses: Research and development 12,088 7,230 22,401 13,971 General and administrative 8,187 4,496 15,918 8,370 Total cost and expenses 20,275 11,726 38,319 22,341 Loss from operations (20,275 ) (11,726 ) (38,319 ) (22,341 ) Other income: Interest income, net 1,107 343 2,356 821 Total other income 1,107 343 2,356 821 Net loss (19,168 ) (11,383 ) (35,963 ) (21,520 ) Comprehensive loss $ (19,168 ) $ (11,383 ) $ (35,963 ) $ (21,520 ) Net loss per share: Basic and diluted net loss per share $ (0.28 ) $ (0.20 ) $ (0.54 ) $ (0.38 ) Weighted average shares used to compute net loss per common share — basic and diluted 67,276 57,180 67,201 57,152 Expand Reconciliation of GAAP to Non-GAAP Financial Measures The following table presents the reconciliation of non-GAAP financial measures to the most directly comparable GAAP financial measures: (In thousands) (Unaudited) Three-Month Periods Ended Six-Month Periods Ended June 30, June 30, 2025 2024 2025 2024 Reconciliation of GAAP to non-GAAP Research and development: GAAP Research and development $ 12,088 $ 7,230 $ 22,401 $ 13,971 Less: Stock-based compensation expense (2,335 ) (1,001 ) (5,097 ) (1,950 ) Less: Depreciation and amortization (44 ) (52 ) (90 ) (105 ) Non-GAAP Research and development $ 9,709 $ 6,177 $ 17,214 $ 11,916 Reconciliation of GAAP to non-GAAP General and administrative: GAAP General and administrative $ 8,187 $ 4,496 $ 15,918 $ 8,370 Less: Stock-based compensation expense (2,854 ) (1,051 ) (5,773 ) (1,861 ) Less: Depreciation and amortization (229 ) (246 ) (466 ) (492 ) Add: Legal settlement — — 590 — Non-GAAP General and administrative $ 5,104 $ 3,199 $ 10,269 $ 6,017 Reconciliation of GAAP to non-GAAP Cost and expenses: GAAP Cost and expenses $ 20,275 $ 11,726 $ 38,319 $ 22,341 Less: Stock-based compensation expense (5,189 ) (2,052 ) (10,870 ) (3,811 ) Less: Depreciation and amortization (273 ) (298 ) (556 ) (597 ) Add: Legal settlement — — 590 — Non-GAAP Cost and expenses $ 14,813 $ 9,376 $ 27,483 $ 17,933 Reconciliation of GAAP to non-GAAP Net loss: GAAP Net loss $ (19,168 ) $ (11,383 ) $ (35,963 ) $ (21,520 ) Add: Stock-based compensation expense 5,189 2,052 10,870 3,811 Add: Depreciation and amortization 273 298 556 597 Less: Legal settlement — — (590 ) — Non-GAAP Net loss $ (13,706 ) $ (9,033 ) $ (25,127 ) $ (17,112 ) Expand
