Altimmune obesity drug candidate lands IND clearance from the FDA

By Jenni Spinner

- Last updated on GMT

(babtab/iStock via Getty Images Plus)
(babtab/iStock via Getty Images Plus)

Related tags Fda IND applications Obesity Phase II Regulation

The pharma firm has announced the agency has approved the company’s investigational new drug application for its Phase II trial of pemvidutide for obesity.

Altimmune—a clinical-stage biopharmaceutical company—has announced the US Food and Drug Administration has cleared the company’s investigational new drug (IND) application for a Phase II clinical trial of pemvidutide. The drug is an investigational GLP-1/glucagon dual receptor agonist under development for the treatment of obesity and non-alcoholic steatohepatitis (NASH).

According to Altimmune representatives, the company expects to initiate the trial sometime in the first quarter of 2022. It previously received IND clearance for pemvidutide in NASH, additionally, Altimmune currently is enrolling patients with nonalcoholic fatty liver disease (NAFLD) in a Phase Ib trial.

Vipin Garg, president and CEO of Altimmune, said this IND approval is good news for patients dealing with severe overweight, as well as the company itself.

Vipin Garg, president and CEO, Altimmune

This Phase II trial in obesity represents an important milestone toward developing a safe and effective treatment option for people with obesity,​” Garg said. “Results from a recently completed Phase 1 study of pemvidutide in Australia showed that 12 weekly subcutaneous doses of pemvidutide at the 1.8 mg dose level resulted in an average weight loss of 10.3% in overweight and obese subjects​.”

He continued, “Importantly, there were no study discontinuations due to adverse events. We believe these results rank among the best in terms of the rate and magnitude of weight loss and tolerability among drugs in development for obesity.​”

The Phase II study, according to Altimmune, will enroll approximately 320 patient participants with obesity, or who are overweight with at least one obesity-related complication. Researchers will randomize subjects 1:1:1:1 to receive either 1.2 mg, 1.8 mg, 2.4 mg pemvidutide, or placebo administered weekly for 48 weeks.

According to researchers, the trial’s primary endpoint is the relative (percent) change in body weight at 48 weeks compared to baseline, with additional readouts including metabolic and lipid profiles, cardiovascular measures, and glucose homeostasis. An interim analysis is planned to assess changes in body weight after 24 weeks of treatment, with an expected readout in the fourth quarter of 2022.

Pemvidutide (proposed INN, formerly known as ALT-801) is a novel, investigational, peptide-based GLP-1/glucagon dual receptor agonist in development for the treatment of obesity and NASH. Activation of the GLP-1 and glucagon receptors is believed to mimic the complementary effects of diet and exercise on weight loss, with GLP-1 suppressing appetite and glucagon increasing energy expenditure.

Altimmune reports that by combining GLP-1 and glucagon activity in a single peptide, pemvidutide has the potential to achieve weight loss comparable to bariatric surgery. The drug also reportedly has been shown to increase the breakdown of fat and its mobilization within the liver, which may have beneficial effects on insulin resistance, a common problem in people with obesity.

Pemvidutide incorporates the EuPort domain, a proprietary technology that (according to Altimmune) increases its serum half-life for weekly dosing while slowing the entry of pemvidutide into the bloodstream, which may improve its tolerability. In a Phase I clinical study, pemvidutide demonstrated striking reductions in body weight, liver fat, and serum lipids.

Related news

Related products

show more

Using Define-XML to build more efficient studies

Using Define-XML to build more efficient studies

Content provided by Formedix | 14-Nov-2023 | White Paper

It is commonly thought that Define-XML is simply a dataset descriptor: a way to document what datasets look like, including the names and labels of datasets...

Related suppliers

Follow us


View more