Alpenglow Biosciences and Coreplus Partner Together to Bring 3D Spatial Biology to Clinical Research and Development

Alpenglow Biosciences (Alpenglow), developers of an innovative end-to-end 3D spatial biology platform, have announced a partnership with CorePlus, a high complexity CLIA-certified clinical and anatomic pathology laboratory, to digitize and analyze tissues in 3D to deliver novel spatial biology insights and accelerate drug development. As part of the partnership, CorePlus will invest an u********** sum into Alpenglow and receive access to Alpenglow’s 3Deep Imager, a patented hybrid open top lightsheet imaging platform.

Mariano de Socarraz, Founder and CEO at CorePlus, said “We continue our quest for innovation and precision diagnostics. We are excited to partner with Alpenglow to incorporate their proprietary 3D spatial biology platform. Having been the first laboratory in the Americas to operationalize AI in prostate cancer, our team sees the value in advancing the transformation in pathology to incorporate 3D technology.”

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Alpenglow has developed a leapfrog technology platform and leads the emerging field of 3D spatial biology with its 3Deep product suite. Leveraging imaging, data processing and analysis, Alpenglow’s 3Deep Imager acts as a flatbed scanner for tissue and generates up to 250 times more data than traditional slide-based pathology yielding much richer datasets and insights used for artificial intelligence and machine learning. Alpenglow’s solution for whole tissue imaging is non-destructive, slide-free and direct to digital.

Dr. Nicholas Reder, MD, MPH and CEO at Alpenglow, said “We are thrilled to partner with CorePlus and bring our 3D spatial biology platform to an innovative laboratory where our automated high-throughput imaging and data processing solutions will create rich datasets to identify 3D biomarkers using machine learning and unlock exciting applications for our pharma partners.”

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Alpenglow and CorePlus aim to leverage 3D datasets to identify 3D biomarkers which could be used to improve patient selection for clinical trials, thereby reducing trial size and accelerating clinical development.

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