AI powered prostate cancer precision medicine

L E A R N M O R E ↓

VISION

To pioneer prostate cancer precision medicine using best in class artificial intelligence for diagnosis, prognosis & treatment guidance

Clinsight is a Swedish company founded in 2022 as a spin out from Karolinska institutet. We pioneer AI powered diagnosis, prognosis and treatment prediction of prostate cancer.

We develop cutting edge deep learning technologies for clinical applications in pathology and oncology with the aim to provide the best possible outcomes for patients diagnosed with prostate cancer.

OUR FOCUS

Is to develop and commercialize AI powered image analysis algorithms which address unmet clinical needs in diagnosis, grading and prognosis of prostate cancer. Our approach is to integrate the algorithms seamlessly into the digital pathology workflow, providing input for pathologists when assessing prostate biopsies for disease.

TECHNOLOGY

We commercialize best in class artificial intelligence systems in prostate pathology by developing state of the art algorithms to be used by pathologists, urologists and oncologists in clinical routine. Our AI systems have been developed by world leading experts in uro-pathology and deep learning, and validated using extensive amounts of data from multiple sites.

Our image analysis platform is

Generalizable

Standardized

Robust

Automated

Quality assured

OUR APPLICATIONS

We develop and commercialize applications for pathologists, urologists and oncologists used in a clinical routine setting to support diagnosis, grading and prognosis for treatment guidance.

Diagnosis & Gleason grading

Support for pathologists in their assessment of cancer extent and Gleason grade in prostate biopsies.

Prognosis of disease

Decision support for urologists and oncologists in treatment guidance of prostate cancer.

TEAM

Nita Mulliqi

Lead AI engineer

M.Sc PhD Student
Karolinska Institutet

Lars Egevad

Chief medical officer
Co-founder

Professor of Pathology Karolinska Institutet

Stefan Almestrand

Chairman of the board
Co-founder

M.Sc

Kimmo Kartasalo

Chief technical officer
Co-founder

D.Sc. (Tech.). Post doctoral scientist Karolinska Institutet

Martin Eklund

Chief scientific officer
Co-founder

Professor of Epidemiology Karolinska Institutet

The utility of artificial intelligence in the assessment of prostate pathology. Egevad L, Strom P, Kartasalo K, Olsson H, Samaratunga H, Delahunt B, Eklund M. Histopathology 2020;76;790-792.
Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading. Egevad L, SwanbergD, Delahunt B, Strom P, Kartasalo K, Olsson H, Berney DM, Bostwick DG, Evans AJ, Humphrey PA, Iczkowski KA, Kench JG, Kristiansen G, Leite KRM, McKenney JK, Oxley J, Pan CC, Samaratunga H, Srigley JR, Takahashi H, Tsuzuki T, van der Kwast T, Varma M, Zhou M, Clements M, Eklund M. Virchows Arch 2020;477;777-786.
Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study. Strom P, Kartasalo K, Olsson H, Solorzano L, Delahunt B, Berney DM, Bostwick DG, Evans AJ, Grignon DJ, Humphrey PA, Iczkowski KA, Kench JG, Kristiansen G, van der Kwast TH, Leite KRM, McKenney JK, Oxley J, Pan CC, Samaratunga H, Srigley JR, Takahashi H, Tsuzuki T, Varma M, Zhou M, Lindberg J, Lindskog C, Ruusuvuori P, Wahlby C, Gronberg H, Rantalainen M, Egevad L, Eklund M. Lancet Oncol 2020;21;222-232.
Prognostic value of perineural invasion in prostate needle biopsies: a population-based study of patients treated by radical prostatectomy. Strom P, Nordstrom T, Delahunt B, Samaratunga H, Gronberg H, Egevad L, Eklund M. J Clin Pathol 2020;73;630-635.
Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists. Bulten W, Balkenhol M, BelingaJA, Brilhante A, Cakir A, Egevad L, Eklund M, Farre X, Geronatsiou K, Molinie V, Pereira G, Roy P, Saile G, Salles P, Schaafsma E, Tschui J, Vos AM, Panel IPIE, van Boven H, Vink R, van der Laak J, Hulsbergen-van der Kaa C, Litjens G. Mod Pathol 2021;34;660-671.
Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies. Egevad L, Delahunt B, Samaratunga H, Tsuzuki T, Olsson H, Strom P, Lindskog C, Hakkinen T, Kartasalo K, Eklund M, Ruusuvuori P. Virchows Arch 2021;478;1109-1116.
The emerging role of artificial intelligence in the reporting of prostate pathology. Egevad L, Delahunt B, Samaratunga H, Tsuzuki T, Yamamoto Y, Yaxley J, Ruusuvuori P, Kartasalo K, Eklund M. Pathology 2021;53;565-567.
Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps. Kartasalo K, Bulten W, Delahunt B, Chen PC, Pinckaers H, Olsson H, Ji X, Mulliqi N, Samaratunga H, Tsuzuki T, Lindberg J, Rantalainen M, Wahlby C, Litjens G, Ruusuvuori P, Egevad L, Eklund M. Eur Urol Focus 2021;7;687-691.
OpenPhi: An interface to access Philips iSyntax whole slide images for computational pathology. Mulliqi N, Kartasalo K, Olsson H, Ji X, Egevad L, Eklund M, Ruusuvuori P. Bioinformatics 2021.
Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer: the PANDA challenge. Bulten W, Cameron Chen PH, Ström P, Pinckaers H, Nagpal K, Cai Y, Steiner DF, van Boven H, Vink R, Hulsbergen-van de Kaa C, van der Laak J, Amin MB, Evans AJ, van der Kwast T, Allan R, Humphrey PA, Grönberg H, Samaratunga H, Delahunt B, Tsuzuki T, Häkkinen T, Egevad L, et al. Nature Medicine 2022; 28;154-163.
Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction. Olsson H, Kartasalo K, Mulliqi N, Capuccini M, Ruusuvuori P, Samaratunga H, Delahunt B, Lindskog C, Janssen EAM, Blilie A; ISUP Prostate Imagebase Expert Panel; Egevad L, Spjuth O, Eklund M. Nat Commun 2022;13;7761
Interobserver Reproducibility of Cribriform Cancer in Prostate Needle Biopsies. Egevad L et al, Histopathology (in press).
Challenges in grading of prostate cancer. Disagreement among expert pathologists and results of artificial intelligence assisted grading. Egevad L, Swanberg O, Delahunt B, Ström P, Kartasalo K, Olsson H, Berney D.M, Bostwick D.G, Evans A.J, Humphrey P.A, Iczkowski K.A, Kench J.G, Kristiansen G, Leite K.R.M, McKenney J, Oxley J, Pan C, Samaratunga H, Srigley J.R, Takahashi H, Tsuzuki T, van der Kwast T, Varma M, Zhou M, Clements M, and Eklund, M. Virchows Arch. 2020, 477(6):777-786
The importance of study design in the application of artificial intelligence methods in medicine. Eklund M, Kartasalo K, Olsson H, and Ström P. npj Digital Medicine, 2019, 2:101.