Apellis Pharmaceuticals, Inc (APLS) Fair Value & Analysis
Healthcare · US · Market cap $5.3B
Fair value as of: Jun 24, 2026
Analysis
Apellis Pharmaceuticals, Inc (APLS) currently trades at $3.51, while our model-based Fair Value estimate is $0.4700 — implying the stock looks roughly 86.6% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Apellis Pharmaceuticals, Inc., a commercial-stage biopharmaceutical company, focuses on the discovery, development, and commercialization of novel therapeutic compounds to treat diseases with high unmet needs. It offers EMPAVELI for the treatment of paroxysmal nocturnal hemoglobinuria; and SYFOVRE for treating geographic atrophy secondary to age-related macular degeneration and geographic atrophy (GA). The company also develops EMPAVELI to treat C3 glomerulopathy and immune complex membranoproliferative glomerulonephritis, focal segmental glomerulosclerosis, and delayed graft function; and APL-3007, a small interfering RNA, or siRNA for the treatment of GA. In addition, it conducts preclinical studies for APL-9099, a treatment targeting the neonatal Fc receptor, or FcRn, which has the potential to be a first-in-class gene editing treatment for future target indications with one-time dosing; and developing other programs with its proprietary in-house capabilities and under its Beam c…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.