diff --git a/Project.toml b/Project.toml
index 4364b41c..8a337614 100644
--- a/Project.toml
+++ b/Project.toml
@@ -3,6 +3,7 @@ uuid = "54578032-b7ea-4c30-94aa-7cbd1cce6c9a"
 version = "0.7.2"
 
 [deps]
+ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 ColPack = "ffa27691-3a59-46ab-a8d4-551f45b8d401"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
@@ -12,6 +13,7 @@ ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [compat]
+ADTypes = "1.2.1"
 ColPack = "0.4"
 ForwardDiff = "0.9.0, 0.10.0"
 NLPModels = "0.18, 0.19, 0.20, 0.21"
diff --git a/docs/Project.toml b/docs/Project.toml
index c8657e93..51be8073 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -25,5 +25,5 @@ Percival = "0.7"
 Plots = "1"
 SolverBenchmark = "0.5"
 SymbolicUtils = "=1.5.1"
-Symbolics = "5.3"
+Symbolics = "5.29"
 Zygote = "0.6.62"
diff --git a/src/ADNLPModels.jl b/src/ADNLPModels.jl
index 481724bb..d3f846b4 100644
--- a/src/ADNLPModels.jl
+++ b/src/ADNLPModels.jl
@@ -3,6 +3,7 @@ module ADNLPModels
 # stdlib
 using LinearAlgebra, SparseArrays
 # external
+using ADTypes: ADTypes
 using ColPack, ForwardDiff, ReverseDiff
 # JSO
 using NLPModels
diff --git a/src/sparse_sym.jl b/src/sparse_sym.jl
index e90c5514..1c04aa00 100644
--- a/src/sparse_sym.jl
+++ b/src/sparse_sym.jl
@@ -1,19 +1,17 @@
 function compute_hessian_sparsity(f, nvar, c!, ncon)
-  Symbolics.@variables xs[1:nvar]
-  xsi = Symbolics.scalarize(xs)
-  fun = f(xsi)
-  if ncon > 0
-    Symbolics.@variables ys[1:ncon]
-    ysi = Symbolics.scalarize(ys)
-    cx = similar(ysi)
-    fun = fun + dot(c!(cx, xsi), ysi)
+  detector = Symbolics.SymbolicsSparsityDetector()  # replaceable
+  function lagrangian(x)
+    cx = zeros(eltype(x), ncon)
+    c!(cx, x)
+    return f(x) + dot(rand(ncon), cx)
   end
-  S = Symbolics.hessian_sparsity(fun, ncon == 0 ? xsi : [xsi; ysi]) # , full = false
+  S = ADTypes.hessian_sparsity(lagrangian, rand(nvar), detector) # , full = false
   return S
 end
 
 function compute_jacobian_sparsity(c!, cx, x0)
-  S = Symbolics.jacobian_sparsity(c!, cx, x0)
+  detector = Symbolics.SymbolicsSparsityDetector()  # replaceable
+  S = ADTypes.jacobian_sparsity(c!, cx, x0, detector)
   return S
 end
 
diff --git a/test/Project.toml b/test/Project.toml
index 0f94a872..1f344a0e 100644
--- a/test/Project.toml
+++ b/test/Project.toml
@@ -10,7 +10,6 @@ NLPModelsTest = "7998695d-6960-4d3a-85c4-e1bceb8cd856"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SparseDiffTools = "47a9eef4-7e08-11e9-0b38-333d64bd3804"
-SymbolicUtils = "d1185830-fcd6-423d-90d6-eec64667417b"
 Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
@@ -25,6 +24,5 @@ NLPModelsModifiers = "0.7"
 NLPModelsTest = "0.10"
 ReverseDiff = "1"
 SparseDiffTools = "2.3"
-Symbolics = "5.3"
-SymbolicUtils = "=1.5.1"
+Symbolics = "5.29"
 Zygote = "0.6"