Is PMCB or PPBT more undervalued in 2026?

CirclFi compares PharmaCyte Biotech, Inc. (PMCB) and Purple Biotech Ltd. (PPBT) using 13 institutional-grade valuation models. PMCB has a Quality of Company score of 5.1/10 while PPBT scores 3.6/10.

Which is a better buy — PMCB or PPBT?

Compare intrinsic values from 13 independent models against current market prices. CirclFi also calculates Value Trap scores. This is not financial advice — conduct your own analysis.

How do PMCB and PPBT valuations compare?

PMCB at $0.86 and PPBT at $2.81 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

PMCB vs PPBT Valuation Comparison 2026 — Intrinsic Value Analysis

PMCB

Biotechnology

PharmaCyte Biotech, Inc.

Quality

5.1

out of 10

Value Trap

SAFE

Price

$0.86

Last close

Models

4/13

Active

PPBT

Biotechnology

Purple Biotech Ltd.

Quality

3.6

out of 10

Value Trap

—

Price

$2.81

Last close

Models

2/13

Active

Model-by-Model Comparison

Model	Type	PMCB Fair Value	PMCB Upside	PPBT Fair Value	PPBT Upside
EROIC Spread	Intrinsic	$2.91	+239.2%	$1.34	-52.3%
First Chicago	Scenario	$5.13	+498.5%	—	—
ML-RIV	Intrinsic	—	—	$0.54	-80.7%
Dynamic NAV	Asset-Based	$2.46	+186.9%	—	—
PWERM	Option-Based	$•••.••	••.•%	$•••.••	••.•%

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PMCB vs PPBT — Which Stock Is More Undervalued?

PMCB scores higher with a 5.1/10 quality rating vs PPBT's 3.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing PharmaCyte Biotech, Inc. (PMCB) and Purple Biotech Ltd. (PPBT) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

PMCB currently trades at $0.86 with a QOC of 5.1/10, while PPBT trades at $2.81 with a QOC of 3.6/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).