Dr.Oz and Dr. Phil and Glycopezil
Executive summary
The product marketed under names like Glycopezil/Glucopezil/Sugar Clean is being promoted through aggressive online ads that use fabricated celebrity endorsements and misleading medical claims; multiple consumer watchdog and review sites identify the campaign as a likely scam and warn against its promises of a “diabetes reversal ritual” [1] [2] [3]. Reports and user complaints describe AI-generated appearances of Dr. Phil and Dr. Oz, contradictory Trustpilot reviews, and regulatory-style advisories urging dispute of charges if consumers have already paid [1] [4] [3].
1. The pitch: a secret “reversal ritual” stitched to celebrity trust
The advertising narrative centers on a supposedly simple home “reversal ritual” for type 2 diabetes that is repeatedly tied to high‑trust names—Dr. Phil McGraw and Dr. Mehmet Oz—and even a fake “60 Minutes” segment; investigations of the ads find no real medical endorsement or legitimate program behind those claims [1] [2]. Ibisik’s reporting notes the ritual is a retention tactic rather than an explained medical protocol and flags comparisons to GLP‑1 drugs like Ozempic or Mounjaro as especially misleading [2].
2. Deepfakes and AI-generated endorsements: the engine of believability
Multiple sources document that the campaign uses AI‑generated videos and audio to manufacture appearances by well‑known doctors and media figures, borrowing their credibility to sell the supplement—an approach explicitly called out by consumer reports and scam trackers [2] [3]. The BBB’s scam tracker records a complaint saying the ad used AI video of Dr. Oz and Dr. Phil and promoted the baseless idea of a parasite causing type 2 diabetes, language that watchdogs label “utter garbage” [3].
3. Consumer reviews: contradictions, likely fakery, and frustration
Public review sites show a mix of short, possibly automated positive posts referencing “Dr. Phill, Oz” gratitude and scathing negative reviews calling the product a phony, with at least one Trustpilot page containing posts that contradict investigative findings about celebrity involvement—an inconsistency that itself matches common scam profiles [4] [5]. Some reviewers explicitly accuse the ads of AI‑generated lies and warn others that refunds were difficult or impossible to secure [5].
4. The medical claims: implausible biology and conflated pharma analogies
Marketing materials claim the drops activate pathways like GLP‑1 drugs, or remove a mythical parasite said to cause diabetes; outlets dissecting the pitch call these claims misleading or baseless, noting there is no scientific evidence presented to support such mechanisms and that the “parasite” narrative is false according to consumer complaints and investigators [2] [3]. Reporting does not provide clinical studies validating the product, and explicit medical endorsements from named doctors are absent from the record [1].
5. How the scam mechanics work and the practical consumer advice reported
Investigations describe typical scam mechanics: long-form retention videos, fake endorsements, anonymous sellers, and disappearing company details that make refunds and accountability difficult; one practical recommendation offered by reporting is to contact card issuers to dispute unauthorized or suspicious charges if payments were already made [1]. The pattern on the sites examined fits many documented supplement scams that trade on urgency and borrowed credibility [1].
6. Competing views and limits of available reporting
While multiple watchdog and review sources converge on the conclusion that Glycopezil‑style ads are deceptive, the material reviewed does not include a company response, formal regulatory action documents, or peer‑reviewed clinical studies proving efficacy—so reporting cannot authoritatively state the full legal status of every seller or the current availability of the product on all platforms [1] [2]. Sources explicitly report fabricated celebrity involvement and consumer complaints, but they do not substitute for formal regulatory findings, which are not present in the dataset provided [3].