Ovarian Cancer Animal Models for Preclinical Studies and Development of Ovarian Cancer Drugs

  • Ni Made Dwi Sandhiutami
  • Puspita Eka Wuyung Departemen Patologi Anatomi, Fakultas Kedokteran Universitas Indonesia
  • Wawaimuli Arozal Departemen Farmakologi dan Terapi, Fakultas Kedokteran Universitas Indonesia
  • Melva Louisa Departemen Farmakologi dan Terapi, Fakultas Kedokteran Universitas Indonesia
  • Deni Rahmat Fakultas Farmasi Universitas Pancasila


Treatment for ovarian carcinoma is still far from optimal, animal models are still needed to study human epithelial ovarian cancer. Animal models of ovarian cancer are very important for understanding the pathogenesis of the disease and for testing new treatment strategies. Ovarian carcinogenesis models in mice have been modified and repaired to produce preneoplastic lesions and neoplastic ovaries that are pathogens resembling human ovarian cancer. Although spontaneous ovarian tumors in mice have been reported, some of the shortcomings of existing studies preclude their use as animal models of ovarian cancer. Because of this, many efforts have been made to develop animal models that are relevant for ovarian cancer. Experimental animal models are developed accurately to represent cellular and molecular changes associated with the initiation and development of human ovarian cancer. Accurate experimental models have significant potential in facilitating the development of better methods for early detection and treatment of ovarian cancer. Several animal models of ovarian cancer have been reported, including manipulation of various reproductive factors or exposure to carcinogens. The latest advance in ovarian cancer modeling is using genetically engineered mice.


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How to Cite
DWI SANDHIUTAMI, Ni Made et al. Ovarian Cancer Animal Models for Preclinical Studies and Development of Ovarian Cancer Drugs. JURNAL ILMU KEFARMASIAN INDONESIA, [S.l.], v. 17, n. 2, p. 139-149, oct. 2019. ISSN 2614-6495. Available at: <http://jifi.farmasi.univpancasila.ac.id/index.php/jifi/article/view/734>. Date accessed: 18 nov. 2019. doi: https://doi.org/10.35814/jifi.v17i2.734.