This article was originally published in Start Up
Unlike for other tissues and organs in the body, no good cell culture model of the liver exists. This difficulty has hampered the discovery of therapeutics for a wide variety of liver diseases-hepatitis, cancer, and cirrhosis, for example-but Hepaticus Inc. is planning to change this: the firm has devised a way to model human liver cell functionality using immunocompetent rats.
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Apart from transplantation, until very recently, there have been no life-saving therapies available for liver failure. Now, one first-generation liver assist device is on the market and others are progressing through both biologic and device clinical trials. Companies with liver assist devices sort into two main groups: companies with dialysis and ultrafiltration systems that improve upon kidney dialysis and fall squarely on the device side of the divide for regulatory purposes, and those that incorporate living cells in a device-biologic combination, which require drug-like approvals. Regardless of the approval process, all companies need compelling efficacy data to convince clinicians and payers of the benefits of a brand new therapy. But the large numbers of variables and unknowns concerning liver function and liver disease have posed considerable obstacles to designing prospective, randomized, controlled clinical trials-a problem highlighted by Circe Biomedical's halting of its large Phase II/III clinical trial for lack of efficacy. There is no question that there is a tremendous need for liver support. What is tantalizing for both companies and investors in this area is that they feel liver assist devices do work-the liver can recover, physiological functions improve, patients with a prognosis of death have survived. But they just haven't been able to prove it yet, not in terms of the only endpoint that really counts at this early stage in the field, improvements in 30-day survival rates.
Current in vivo and in vitro models can't keep up with the demand for the safety assessment of large numbers of compounds emerging from high-throughput strategies. Pharmaceutical companies and start-ups are therefore building new systems that they hope will be capable of predicting the toxicity liabilities of new compounds. Cheminformatics can help week out toxic compounds at the lead selection and optimization stage; toxicogenomics may provide a toxicity diagnostic capability at all stages of drug development. For both toxicology approaches, there is not yet enough high quality data to build predictive models. Toxicology-focused cheminformatics programs attempt to consolidate data from hitherto untapped sources; toxicogenomics companies are engaged in the fussy and expensive process of manufacturing data from scratch and validating them with biological experiments.
Every venture capitalist is anxious to use the latest IPO window to get his companies liquid. But some firms are more successful than others. At the top of the list there were few surprises--JP Morgan Partners and Alta Partners, with six biotech IPOs each, and MPM Capital with five. But the next group down contained some newer names.