Altimmune, Inc. (ALT) CEO Vipin K. Garg on Q1 2022 Results - Earnings Call Transcript

Altimmune, Inc. (NASDAQ:ALT) Q1 2022 Earnings Conference Call May 12, 2022 8:30 AM ET

Company Participants

Vipin K. Garg – President and Chief Executive Officer
Richard Eisenstadt – Chief Financial Officer
Scot Roberts – Chief Scientific Officer
Scott M. Harris – Chief Medical Officer

Conference Call Participants

Seamus Fernandez – Guggenheim Partners
Yasmeen Rahimi – Piper Sandler Companies
Liisa Bayko – Evercore ISI
Mayank Mamtani – B. Riley Securities
Jonathan Wolleben – JMP Securities LLC

Operator

[Operator Instructions] Good day, ladies and gentlemen, and welcome to the Altimmune, Inc. Q1 Earnings Conference all. At this time, all participants are in a listen-only mode. Later we will conduct a question-and-answer session and instructions will follow at that time. If anyone should require Operator assistance, [Operator Instructions]. As a reminder, this call is being recorded. I would now like to introduce your host for today's conference call. Richard Eisenstadt, Chief Financial Officer of Altimmune. Richard you may begin.

Richard Eisenstadt

Thank you, Katy. And good morning, everyone. Thank you for participating in Altimmune First Quarter 2022 Earnings Conference Call. Members of the Altimmune team joining me on the call today are Vipin K. Garg, our Chief Executive Officer, Scot Roberts, our Chief Scientific Officer, and Scott Harris, our Chief Medical Officer. Following the prepared remarks, we will hold a question-and-answer session. A press release with our first-quarter 2022 financial results was issued this morning and can be found on the Investor Relations section of the company's website.

Before we begin, I would like to remind everyone that remarks about future expectations, plans, and prospects constitute forward-looking statements for purposes of Safe Harbor provisions under the Private Securities Litigation Reform Act of 1995. Altimmune cautions that these forward-looking statements are subject to risks and uncertainties that could cause actual results to differ materially from those indicated.